Cursor AI
Inline Editing and Debugging
Demo Inline AI Edits
In this guide, you’ll learn how to use inline AI-assisted editing directly within your code editor. We’ll compare two common modes—separate chat windows versus inline prompts—and demonstrate how inline editing can streamline your workflow and reduce context switching.
Why Inline AI Editing?
- Keeps you in the flow of coding
- Provides suggestions as diffs you can accept or reject
- Accelerates prototyping, refactoring, and helper-function generation
Note
Inline prompts work best for focused, localized changes. For broad design discussions, consider a separate chat to maintain context.
Example: Simple Flask Authentication
Below is a minimal Flask app that demonstrates password hashing, an authentication decorator, and basic routes. We’ll use this code to show inline AI-powered enhancements.
# app.py
import hashlib
import functools
from flask import Flask, request, session, redirect, url_for, flash
app = Flask(__name__)
app.secret_key = 'your-secret-key'
def hash_password(password: str) -> str:
"""Simple password hashing (not secure for production)."""
return hashlib.sha1(password.encode()).hexdigest()
def login_required(view):
"""Decorator to ensure a user is logged in."""
@functools.wraps(view)
def wrapped_view(**kwargs):
if 'user_id' not in session:
return redirect(url_for('login'))
return view(**kwargs)
return wrapped_view
@app.route('/')
def index():
if 'user_id' in session:
return redirect(url_for('dashboard'))
return redirect(url_for('login'))
@app.route('/register', methods=['GET', 'POST'])
def register():
error = None
if request.method == 'POST':
username = request.form.get('username', '').strip()
password = request.form.get('password', '').strip()
if not username:
error = 'Username is required.'
elif not password:
error = 'Password is required.'
else:
# Insert user into the database...
pass
return f"Register Page. Error: {error}"
Warning
Using SHA-1 for password hashing is not secure for production. Consider bcrypt
or scrypt
for real-world applications.
Inline Prompt vs Separate Chat
Most AI coding tools offer two modes. Choose based on your task:
Mode | Shortcut | Best Use Cases |
---|---|---|
Separate Chat | Command L / Ctrl L | Deep discussions, design reviews, large refactors |
Inline Prompt | Command K / Ctrl K | Quick edits, helper functions, localized refactoring |
Generating a Helper Function Inline
- Highlight the code location.
- Invoke the inline prompt (⌘-K / Ctrl-K).
- Ask for a helper function, e.g., “Create a function to reverse a string.”
The AI will generate:
def reverse_string(s: str) -> str:
"""
Reverses a string.
Args:
s (str): The string to reverse.
Returns:
str: The reversed string.
"""
return s[::-1]
Green lines indicate additions; red lines show removals. Press ⌘-Y / Ctrl-Y to accept or ⌘-N / Ctrl-N to reject.
Evolving Code with Inline Edits
You can request optimizations or new features inline. For example, add logging and error handling to your login_required
decorator:
def login_required(view):
"""Decorator to ensure a user is logged in, with logging and error handling."""
@functools.wraps(view)
def wrapped_view(**kwargs):
try:
if 'user_id' not in session:
app.logger.warning(f"Unauthorized access attempt to {request.path}")
flash("Please log in to access this page", "error")
return redirect(url_for('login'))
return view(**kwargs)
except Exception as e:
app.logger.error(f"Error in login_required decorator: {e}")
flash("An unexpected error occurred. Please try again.", "error")
return redirect(url_for('login'))
return wrapped_view
By refining code inline, you maintain momentum and iterate faster on performance, security, and feature improvements.
When to Use Each Mode
- Separate Chat
- Deep architectural discussions
- Reviewing or documenting large codebases
- Inline Prompt
- Fast helper functions
- Small bug fixes or refactors
- Localized testing and debugging
Experiment with both to find the balance that boosts your productivity and minimizes context switching.
Links and References
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