Debugging Python Scripts with AI in Antigravity
Debugging Python Scripts with AI in Antigravity
We've all been there.
`print(“here”)`
`print(“here 2”)`
`print(variable)`
Debugging Python scripts can be a tedious game of hide-and-seek. But in Google Antigravity, the debugger has a brain.
The AI Debugger
Antigravity doesn't just show you the stack trace; it understands it.
1. The “Fix This” Button
When your Python script crashes with an exception (e.g., `IndexError: list index out of range`), Antigravity highlights the line and offers a “Fix This” button.
Clicking it prompts the AI to:
1. Analyze the error.
2. Read the surrounding code.
3. Propose a fix (e.g., “Check if list is empty before accessing index 0”).
2. Natural Language Breakpoints
Instead of clicking in the gutter to set a breakpoint at line 42, you can tell the debugger:
> “Pause execution when `user_count` becomes negative.”
The AI inserts a conditional breakpoint for you.
3. Conversational Variable Inspection
When paused at a breakpoint, you don't need to dig through the “Variables” pane. Just ask the Chat:
> “Why is `total_price` returning NaN?”
The AI inspects the current memory state, traces the variable back, and might say:
> “`total_price` is NaN because `tax_rate` is currently `None`. It was passed as `None` from the `calculate_tax` function.”
Example: Debugging a Flask Route
Imagine a Flask API that returns a 500 error.
1. Run with Debugger: Press F5.
2. Trigger Error: Send the request.
3. AI Analysis: The AI automatically intercepts the 500 error.
> “It looks like you're trying to access `request.json['email']` but the request body is empty. You should add a check for `request.is_json`.”
4. Auto-Fix: You click “Apply Fix,” and the AI wraps the code in a `try/except` block or adds the validation logic.
Conclusion
Debugging is no longer a solitary struggle. With Antigravity, you have a senior Python engineer sitting next to you, watching your code run, and pointing out exactly where things went wrong.
At BYS Marketing, we use AI debugging to slash our troubleshooting time by 70%, allowing us to focus on building features, not fixing bugs.
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