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如何在Visual Studio Code中对Python脚本的单个片段进行执行与调试?

Add Cell-like Execution & Debugging to .py Files in VS Code

Absolutely! You've got a few solid options to replicate Jupyter Notebook's cell-based workflow in regular .py files within VS Code—no need to switch file types. Here's how to do it:

1. Use Python Interactive Window with Cell Markers

This is the closest you'll get to Jupyter's cell experience, and it's built into VS Code's Python tooling (with the Jupyter extension installed):

  • Add # %% at the start of any code block you want to treat as a "cell". VS Code will automatically recognize this and show a Run Cell button next to the line.
  • Clicking "Run Cell" executes that block in an interactive window, where variables persist across cell runs—just like in a notebook.
  • For debugging: Set breakpoints within the cell, then click the Debug Cell button (it appears next to "Run Cell" when you hover) to step through the code line by line.

2. Run/Debug Selected Code Snippets

If you don't want to add cell markers, you can work directly with arbitrary code sections:

  • Highlight the code block you want to execute, then right-click and select Run Selection/Line in Python Terminal—this runs only the selected code in the integrated terminal.
  • For debugging highlighted code: Right-click the selection and choose Debug Selection. VS Code will launch a debug session focused solely on that snippet, letting you set breakpoints, inspect variables, and step through execution.

3. Enable Persistent Interactive Sessions

Once you run a cell or selected code, the interactive window (or terminal) maintains your session state. You can:

  • Type additional code directly into the interactive window to test quick ideas.
  • Use the "Restart Kernel" button in the interactive window to reset all variables if you need a fresh start.

A quick note: Make sure you have the Jupyter extension installed in VS Code (it's part of the recommended Python extension pack) — most of these cell-based features rely on it.

Hope these methods give you the flexibility you need while keeping your code in .py files! 🚀

内容的提问来源于stack exchange,提问作者banana_99

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最近更新时间:2026.04.29 22:47:28