How does ChatGPT compare to GitHub Copilot when it comes to getting help writing code? Is one better than the other? For ChatGPT, have people learned any good prompt design to get excellent code results?
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I'm using both of them for my learning-Rust project at the moment, notes in my issues here: github.com/simonw/advent-
ChatGPT will write entire scripts based on a short prompt - Copilot tends to more work one line (or block) at a time
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If we assume the Centaur model for pairing these tools with people, any tips you’ve learned when working with ChatGPT so far for programming tasks?
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Best results I have had so far are with prompts that look like this
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Using ChatGPT to write a scraper API for ChatGPT
fedi.simonwillison.net/@simon/1094518
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![Me: Use Python and Playwright to build a Flask API which opens https://chat.openai.com/ and inserts text into the input box on it and then waits 10 seconds and returns the contents of the last div.ConversationItem__Message element on the page
from flask import Flask, jsonify
from playwright import sync_playwright
app = Flask(__name__)
@app.route('/insert_text', methods=['POST'])
def insert_text():
text = request.form.get('text')
with sync_playwright() as p:
browser = p.chromium.launch()
page = browser.new_page()
page.goto('https://chat.openai.com/')
input_box = page.query_selector('input[type="text"]')
input_box.fill(text)
page.wait_for_timeout(10000)
message = page.query_selector('div.ConversationItem__Message')
return jsonify({ 'message': message.inner_text })
if __name__ == '__main__':
app.run()](https://pbs.twimg.com/media/FjFZCPWVUAAJBoM?format=jpg&name=large)
read image description
ALT
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Out of curiosity, I saw in your code you're using just. How do you like it, and why use just over make or something Python-based like pyinvoke.org. I've been looking for alternatives to make.
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I switched to "cargo run" now, but I have a few notes on why I like Just here
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