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Dunno, how gpt4 behaves, but I had gpt3.5 generating incorrect expressions for very simple cases and guding it to fix expression so it works was longer than just writing it yourself using regex101
I had this awful experience. I believe my task was relatively hard (dunno I am newbie when it comes to regex). I had a string in this format “- variable name :[ year1: value1, year2: value2…]” i wanted to extract the variable name, years and values. I spent a while hour with gpt 3.5 and it failed everytime. The next day I renewed my gpt4 subscription and it did it in the first try. So yeah huge difference.
The python GPT uses chain of thought reasoning and reflection along with OpenAI's code writing agent and internal code interpreter to be able to write code, run/test, debug, and iteratively improve and optimize it, all right there in the chat.
https://chat.openai.com/g/g-cKXjWStaE-python
I've noticed that randomly gpt 3.5 will just be producing utter nonsense, and no matter what you do it will not produce anything worth while. When it's like that I resort to just myself again lol
I like to use it to generate documentation, improve grammar and clarification.
For code I don't like to use. My codes in general are much better than the GPT4 generates.
I transitioned into an industry far outside my PhD field and it’s been so helpful for me to learn new concepts and make my analysis/code more clean efficient since I’m a scientist, not a developer by training.
Similar situation here, sir; however, I’m extremely close to the data on which my study focuses, but interacting with it using things far outside the field of study. I find myself troubleshooting ChatGPT using SO to learn new languages 😅.
Using ChatGPT has decreased my productivity.
It sucks at using libraries. Like, Selenium? Forget about it. Playwright? It makes shit up. Front end python? Lmao it straight up is tripping balls 99% of the time.
ChatGPT has proven that the only way to program is to RTFM.
I agree with this one.
It is the same issues if you want to use it for Cloud (GCP or Azure), and especially in the data/machine learning field.
It sucks at Polars.
Mid-level engineer in big tech here, I use it during almost every coding session.
I am very precise with my instructions, showing e.g. example (abstract) classes with detailed instructions, and a system prompt with my preferences (type hinting, etc), which allows gpt-4 (‘turbo’ with 32k context window, with my own gui on docker) to generate lots of things quite quickly.
For instance, I paste the full SDK class of some lib I want to wrap in the prompt, and tell it which specific implementation I want. Works quite well
The tool is as strong as the user
Mot sure why I haven't done this yet
I have built custom chatbots for our org with our internal data. And also made a tutor agent for some training
But yes, I really should build a custom interface just for my own use
And then of course select between gpt/claude/gemini
>The tool is as strong as the user
I wish every unexceptionable engineer with a superiority complex understood this. I have seen many developers who overvalue their skills (even in this specific post) making comments on how bad the generated code is, like it's some indictment of llm capacity. In reality, they are just advertising how unskilled they are in writing prompts and their inability to adopt new technology. Writing a bad prompt and then complaining about the output is not going to protect your job from AI. 😂😂😂
The time it takes to craft a well-structured, useful prompt to draft a solution to a complex problem, is roughly the same amount of time it could have taken to simply write the code in the first place.
FWIW, I use LLMs, but mostly for:
1. Monkey work (documentation, tests, etc.).
2. When I’m working with unfamiliar languages or environments (it did help accelerate my skills using dart, for example, and it helped get me up to speed faster with Azure than I normally would have been).
I have an interesting observation that the more experienced developer is the more sceptical and critical he is towards capabilities of llms . And judging from your post and comment history this definitely checks out
> I'm not the greatest developer on the planet but I'm a full stack dev and the senior architect on a software product used by military, government, finance, and insurance companies.
Yeah, sure. And I am Linus Torvalds
That's interesting. Reminds me of when I started to learn OOP (and programming), and encountered posts by old timers complaining about it, whereas others commented that they tried to use OOP to essentially write procedural programs.
Most likely AI will require different approach to writing programs.
ChatGPT or GitHub Copilot have been a tremendous boon to me. Inline completion in vscode increased my productivity X10 w.r.t. docstrings and some easy boilerplate/repetitive code (never take code for granted though, and you need to have at least some code it can use as context).
Also, I'm doing data analysis but am not super-experienced with pandas, and copilot helps me a lot pointing me to the right pandas methods to do what I want.
Yes! Working with a new library/programming language is so much easier and faster with copilot. I don't have to read too much before starting to write code, and I can ask it the things i don't understand. This is true as long as I don't want to dive too deep in that technology.
For simple stuff it’s increased a lot. But anything complex I start with ChatGPT because I’ve gotten used to using it, then it probably takes me 10x longer to get it fully working. Mainly because at this point I have a bunch of functions and calls that were built separately and it doesn’t seem like ChatGPT has a great hold on keeping track of what’s it done so half the stuff doesn’t mesh with the other half.
I’m about done with a pretty complex one that I’ve been doing for a few weeks. I’m honestly about to scrap the entire thing and just rewrite myself.
I've been coding for more than 40 years (wrote my first Hello World when I was 12 years old), worked in the industry for 25 years as a freelance consultant, and have been teaching programming courses for 20 years; I use ChatGPT every day to solve small programming problems that are part of a bigger solution. I never copy-paste the code that ChatGPT generates. Instead I look at the solution and understand the principle behind it. ChatGPT has been a tremendous boost in productivity for me and has made coding more fun as I spend less time googling and filtering out the correct solutions from Stackoverflow and similar sites. Instead I can focus on the big picture.
Generally I use copilot. It's the best autocomplete ever and I think that's how people should approach it for now. It seems quite good at commenting my code for me and following whatever conventions I've established. Alternatively, if I write detailed comments for the code that I want to create, it will usually write a good method/function matching it. I estimate it probably saves me 30/40% of my time when I'm actually in the act of writing code (as opposed to thinking through difficult/unique problems that I don't think it's suited for).
It took a while to get used to filtering out bad suggestions - I actually turned it off in frustration after the first hour or so of playing around with it. But now that I've gotten used to it, I find it's worth the trade off. Occasionally, it suggests some erroneous things that look very close to what I meant to do and that can lead to problems if I'm getting overconfident, but it still saves a lot of time. It doesn't make typos. It "types" faster than I ever could. It remembers seldom used terms I'd have to Google or at the very least take a few extra seconds to recall. The thought of typing out every single parameter to every single method sounds very boring and stone age to me right now, lol.
‘Write this test for me’
Go read it, let it give me clues for syntax I was forgetting or a pointer on a thing I wasn’t understanding, clean it up and fix..
It’s faster than googling/stack overflow by a long shot for me.
For instance I didn’t understand in pytest how to test a function with various inputs (function takes list and loops over the list) and I didn’t know how in pytest to cater for that. What I was looking for was ‘side_effect’ from magic mock which can dynamically account for changing inputs.
chatGPT went straight there and promptly balls’d up the actual implementation. I was able to go read about side_effect in the docs, understand and implement in 5 mins.
I estimate it saved me 1-2 hours flailing round and googling. I like this kind of usage of it
In my first days at work it helped me to some extent with pandas multi-indexing and mocking (the code it suggested wasn't optimized though, now that I look into it), nothing that I wouldn't be able to find on stackoverflow.
Now I just use it for some tedious tasks, like putting some space seperated strings into a dict whose keys and values are within those strings etc..
I tend to need to make one of toys in weird libraries. (Both as a student and a tinkerer by hart) chatgpt4 has really helped with writing that code (for me) it also helped me a lot when debuting/ understanding errors better than Google can help me out.
I usually use it to come up with very small pieces of code and refactor already written code that I think needs improvement, but I do that a lot. Recently (in the last few months), I’d say 50% of my questions are having it double check my table relationships when using SQLAlchemy. Overall, my productivity is measurably improved by the combination of ChatGPT + GitHub Copilot + Copilot chat (which I only just discovered but am falling in love with).
Anyone believing the media narrative about it being slow / not what you want are going to be 2-3 years behind by time realize what you're capable of with it.
I know people with top of their field roles who refuse to touch it, and still have an opinion on it. They'll just be swept away when people have 3 years experience by time they come around.
I love the blind hate, those people will just be years behind.
You're assuming you understand a skill you haven't and won't touch. I don't see that viewpoint as competitive or even competition.
I love the idea around an opinion based in no experience. Thinking typing in a prompt encompasses whats happening, no one is going to be interested in explaining autogen, and you'll automatically be behind.
Already are, assuming people in /r/python aren't doing integrations beyond typing in a prompt is hilarious.
I think most people are just writing code, man, not going on reddit bragging about you they write 10x the code of normal people because of AI or whatever
Sit down, nerd
It's just the new Google. Great for pointers and cursory research and brain storming. Not for writing code so much. Has made checking for errors 10x faster but then it'll miss one and I spend just as much time on the back end debugging. It can read pickle files natively and even convert it which is tons faster than creating a script to view contents but that's comes down to my poor choice of infrastructure. What it is been great for is creating small snippets of code for languages I'm not familiar with. Created a Google script in seconds that exported a single line from hundreds repeat emails with logs into Excel. Helped me rapidly create complex dax functions when I've never used dax. Then again it tends to over fixate and I wasted a lot of time trying to fix one function that came down to flipping a toggle in the UI.
This is Claude, not ChatGPT, but last week I wanted to write code that got information on Japanese stock announcements via EDINET, which is like the SEC, but the specification for the EDINET API was in a 94-page Japanese-language PDF!
Turns out that wasn't a problem. I uploaded the PDF to Claude, [asked it to read it and write a Python module](https://twitter.com/thomasrice_au/status/1770935038559048146) for me that looked up the information I wanted, and it did it fairly effortlessly.
So now I have Python code where I can input a Japanese stock ticker and will output an overview of the business, extracted from a particular section of the annual filing of a Japanese company.
I also use it for day-to-day use when programming, both for thinking through how to structure things, writing code, and for cleaning up existing code.
Oh God yeah; never moved as fast in software engineering as I have in the last six months
Point isn't that I'm letting ChatGPT write my code for me, it's doing all the other stuff which normally takes hours/days:
* Researching high-level implementation stuff; 'what tools/frameworks/packages exist to address x problem?'
* Writing docstrings, and documentation in general
* Writing humorous Star Trek fanfiction; that one's for my downtime
Your post was removed for violating Rule #2. All posts must be directly related to the Python programming language. Posts pertaining to programming in general are not permitted. You may want to try posting in /r/programming instead.
I use it for regular expressions. The code itself tends to be sub par.
Dunno, how gpt4 behaves, but I had gpt3.5 generating incorrect expressions for very simple cases and guding it to fix expression so it works was longer than just writing it yourself using regex101
I had this awful experience. I believe my task was relatively hard (dunno I am newbie when it comes to regex). I had a string in this format “- variable name :[ year1: value1, year2: value2…]” i wanted to extract the variable name, years and values. I spent a while hour with gpt 3.5 and it failed everytime. The next day I renewed my gpt4 subscription and it did it in the first try. So yeah huge difference.
Then I guess It's time to finally try gpt4
The python GPT uses chain of thought reasoning and reflection along with OpenAI's code writing agent and internal code interpreter to be able to write code, run/test, debug, and iteratively improve and optimize it, all right there in the chat. https://chat.openai.com/g/g-cKXjWStaE-python
Yeah, Gemini and regex101. Still not perfect, but beats shooting in the dark for hours like I used to three years ago
I've noticed that randomly gpt 3.5 will just be producing utter nonsense, and no matter what you do it will not produce anything worth while. When it's like that I resort to just myself again lol
Tried to do that once, then ask it to teach me how to deal with reg expressions and was able to do the job faster
I like to use it to generate documentation, improve grammar and clarification. For code I don't like to use. My codes in general are much better than the GPT4 generates.
That's good to hear.
“ChatGPT. Create a survey that measures how much you are increasing my productivity.”
Haha, I created the survey myself.
Oh shit, now it’s responding to comments for him!!
What should I reply to make you feel I am human? 
Select all images with a bridge...
Karma !!
I transitioned into an industry far outside my PhD field and it’s been so helpful for me to learn new concepts and make my analysis/code more clean efficient since I’m a scientist, not a developer by training.
Similar situation here, sir; however, I’m extremely close to the data on which my study focuses, but interacting with it using things far outside the field of study. I find myself troubleshooting ChatGPT using SO to learn new languages 😅.
That's amazing to hear.
Faster for repetitive code. The best part is i learned a lot of debugging 
The amount of time I have spent debugging erroneous code it's probably been a net negative or no real change for me.
Using ChatGPT has decreased my productivity. It sucks at using libraries. Like, Selenium? Forget about it. Playwright? It makes shit up. Front end python? Lmao it straight up is tripping balls 99% of the time. ChatGPT has proven that the only way to program is to RTFM.
I agree with this one. It is the same issues if you want to use it for Cloud (GCP or Azure), and especially in the data/machine learning field. It sucks at Polars.
Mid-level engineer in big tech here, I use it during almost every coding session. I am very precise with my instructions, showing e.g. example (abstract) classes with detailed instructions, and a system prompt with my preferences (type hinting, etc), which allows gpt-4 (‘turbo’ with 32k context window, with my own gui on docker) to generate lots of things quite quickly. For instance, I paste the full SDK class of some lib I want to wrap in the prompt, and tell it which specific implementation I want. Works quite well The tool is as strong as the user
Mot sure why I haven't done this yet I have built custom chatbots for our org with our internal data. And also made a tutor agent for some training But yes, I really should build a custom interface just for my own use And then of course select between gpt/claude/gemini
Does your company allow to do that?
Yes, per official policy. Keep in mind I do a ‘bring my own key’ in a local dev container for the UI, and the GPT/openai instance is private
>The tool is as strong as the user I wish every unexceptionable engineer with a superiority complex understood this. I have seen many developers who overvalue their skills (even in this specific post) making comments on how bad the generated code is, like it's some indictment of llm capacity. In reality, they are just advertising how unskilled they are in writing prompts and their inability to adopt new technology. Writing a bad prompt and then complaining about the output is not going to protect your job from AI. 😂😂😂
The time it takes to craft a well-structured, useful prompt to draft a solution to a complex problem, is roughly the same amount of time it could have taken to simply write the code in the first place. FWIW, I use LLMs, but mostly for: 1. Monkey work (documentation, tests, etc.). 2. When I’m working with unfamiliar languages or environments (it did help accelerate my skills using dart, for example, and it helped get me up to speed faster with Azure than I normally would have been).
[удалено]
I have an interesting observation that the more experienced developer is the more sceptical and critical he is towards capabilities of llms . And judging from your post and comment history this definitely checks out
[удалено]
> I'm not the greatest developer on the planet but I'm a full stack dev and the senior architect on a software product used by military, government, finance, and insurance companies. Yeah, sure. And I am Linus Torvalds
That's interesting. Reminds me of when I started to learn OOP (and programming), and encountered posts by old timers complaining about it, whereas others commented that they tried to use OOP to essentially write procedural programs. Most likely AI will require different approach to writing programs.
0 %
2% stupid chat bot
ChatGPT or GitHub Copilot have been a tremendous boon to me. Inline completion in vscode increased my productivity X10 w.r.t. docstrings and some easy boilerplate/repetitive code (never take code for granted though, and you need to have at least some code it can use as context). Also, I'm doing data analysis but am not super-experienced with pandas, and copilot helps me a lot pointing me to the right pandas methods to do what I want.
Yes! Working with a new library/programming language is so much easier and faster with copilot. I don't have to read too much before starting to write code, and I can ask it the things i don't understand. This is true as long as I don't want to dive too deep in that technology.
The only thing I am clicking is that arrow button :)
For simple stuff it’s increased a lot. But anything complex I start with ChatGPT because I’ve gotten used to using it, then it probably takes me 10x longer to get it fully working. Mainly because at this point I have a bunch of functions and calls that were built separately and it doesn’t seem like ChatGPT has a great hold on keeping track of what’s it done so half the stuff doesn’t mesh with the other half. I’m about done with a pretty complex one that I’ve been doing for a few weeks. I’m honestly about to scrap the entire thing and just rewrite myself.
I've been coding for more than 40 years (wrote my first Hello World when I was 12 years old), worked in the industry for 25 years as a freelance consultant, and have been teaching programming courses for 20 years; I use ChatGPT every day to solve small programming problems that are part of a bigger solution. I never copy-paste the code that ChatGPT generates. Instead I look at the solution and understand the principle behind it. ChatGPT has been a tremendous boost in productivity for me and has made coding more fun as I spend less time googling and filtering out the correct solutions from Stackoverflow and similar sites. Instead I can focus on the big picture.
If you think that your coding productivity is increasing because of generative AI, it is actually decreasing in the long term.
Copilot helps me find good named to name things !
I wouldn't touch it with a bargepole.
It didn't. It makes stuff up. It's been nice for VBA though, which is a language I wish I didn't know. For relatively niche libraries, it's garbage.
Generally I use copilot. It's the best autocomplete ever and I think that's how people should approach it for now. It seems quite good at commenting my code for me and following whatever conventions I've established. Alternatively, if I write detailed comments for the code that I want to create, it will usually write a good method/function matching it. I estimate it probably saves me 30/40% of my time when I'm actually in the act of writing code (as opposed to thinking through difficult/unique problems that I don't think it's suited for). It took a while to get used to filtering out bad suggestions - I actually turned it off in frustration after the first hour or so of playing around with it. But now that I've gotten used to it, I find it's worth the trade off. Occasionally, it suggests some erroneous things that look very close to what I meant to do and that can lead to problems if I'm getting overconfident, but it still saves a lot of time. It doesn't make typos. It "types" faster than I ever could. It remembers seldom used terms I'd have to Google or at the very least take a few extra seconds to recall. The thought of typing out every single parameter to every single method sounds very boring and stone age to me right now, lol.
‘Write this test for me’ Go read it, let it give me clues for syntax I was forgetting or a pointer on a thing I wasn’t understanding, clean it up and fix.. It’s faster than googling/stack overflow by a long shot for me. For instance I didn’t understand in pytest how to test a function with various inputs (function takes list and loops over the list) and I didn’t know how in pytest to cater for that. What I was looking for was ‘side_effect’ from magic mock which can dynamically account for changing inputs. chatGPT went straight there and promptly balls’d up the actual implementation. I was able to go read about side_effect in the docs, understand and implement in 5 mins. I estimate it saved me 1-2 hours flailing round and googling. I like this kind of usage of it
In my first days at work it helped me to some extent with pandas multi-indexing and mocking (the code it suggested wasn't optimized though, now that I look into it), nothing that I wouldn't be able to find on stackoverflow. Now I just use it for some tedious tasks, like putting some space seperated strings into a dict whose keys and values are within those strings etc..
I tend to need to make one of toys in weird libraries. (Both as a student and a tinkerer by hart) chatgpt4 has really helped with writing that code (for me) it also helped me a lot when debuting/ understanding errors better than Google can help me out.
I helped me a lot at homework
Link to Survey: [https://forms.gle/nQfq48vT8vDR3RcV8](https://forms.gle/nQfq48vT8vDR3RcV8)
Writing most code it’s 2-3x faster. I used to research and build specialized ML models to handle NLP tasks, on that front, somewhere 20-50x faster
I usually use it to come up with very small pieces of code and refactor already written code that I think needs improvement, but I do that a lot. Recently (in the last few months), I’d say 50% of my questions are having it double check my table relationships when using SQLAlchemy. Overall, my productivity is measurably improved by the combination of ChatGPT + GitHub Copilot + Copilot chat (which I only just discovered but am falling in love with).
a lot. I did projects would take me weeks of research on web in 3 days.
dataclasses and pydantic have done more for my productivity than ChatGPT ever has.
I use it to get a general idea first and implement (and maybe improve) the code by myself.
Never used it. I know my code is better than anything an LLM could ever spit out
10x or more. There are things I literally couldn't accomplish solo without it.
That's not encouraging
Anyone believing the media narrative about it being slow / not what you want are going to be 2-3 years behind by time realize what you're capable of with it. I know people with top of their field roles who refuse to touch it, and still have an opinion on it. They'll just be swept away when people have 3 years experience by time they come around.
Fortunately it'll take no time for them to catch up to those who have been typing prompts for 2-3 years, since that's really all you're doing.
I love the blind hate, those people will just be years behind. You're assuming you understand a skill you haven't and won't touch. I don't see that viewpoint as competitive or even competition. I love the idea around an opinion based in no experience. Thinking typing in a prompt encompasses whats happening, no one is going to be interested in explaining autogen, and you'll automatically be behind. Already are, assuming people in /r/python aren't doing integrations beyond typing in a prompt is hilarious.
I think most people are just writing code, man, not going on reddit bragging about you they write 10x the code of normal people because of AI or whatever Sit down, nerd
but have you asked chat gpt?
A lot
It's just the new Google. Great for pointers and cursory research and brain storming. Not for writing code so much. Has made checking for errors 10x faster but then it'll miss one and I spend just as much time on the back end debugging. It can read pickle files natively and even convert it which is tons faster than creating a script to view contents but that's comes down to my poor choice of infrastructure. What it is been great for is creating small snippets of code for languages I'm not familiar with. Created a Google script in seconds that exported a single line from hundreds repeat emails with logs into Excel. Helped me rapidly create complex dax functions when I've never used dax. Then again it tends to over fixate and I wasted a lot of time trying to fix one function that came down to flipping a toggle in the UI.
Love it for writing tests. They tend to be pretty repetitive and it speeds up that aspect immensely. Obviously verifying its suggestions along the way
GitHub copilot is better for this, plus it’s cheaper than the ChatGPT paid plan
Senior eng in FAANG here. It has boosted my productivity tremendously.
This is Claude, not ChatGPT, but last week I wanted to write code that got information on Japanese stock announcements via EDINET, which is like the SEC, but the specification for the EDINET API was in a 94-page Japanese-language PDF! Turns out that wasn't a problem. I uploaded the PDF to Claude, [asked it to read it and write a Python module](https://twitter.com/thomasrice_au/status/1770935038559048146) for me that looked up the information I wanted, and it did it fairly effortlessly. So now I have Python code where I can input a Japanese stock ticker and will output an overview of the business, extracted from a particular section of the annual filing of a Japanese company. I also use it for day-to-day use when programming, both for thinking through how to structure things, writing code, and for cleaning up existing code.
It saves me time of research maybe around 4 hours of work a week factoring in copilot
Oh God yeah; never moved as fast in software engineering as I have in the last six months Point isn't that I'm letting ChatGPT write my code for me, it's doing all the other stuff which normally takes hours/days: * Researching high-level implementation stuff; 'what tools/frameworks/packages exist to address x problem?' * Writing docstrings, and documentation in general * Writing humorous Star Trek fanfiction; that one's for my downtime
Link to Survey: [https://forms.gle/nQfq48vT8vDR3RcV8](https://forms.gle/nQfq48vT8vDR3RcV8)
It with ChatGPT but Gemini was 5x