PyLiveView — Live Python Values in VS Code

PyLiveView brings live, inline Python values and errors directly into your editor as you type. It helps you explore code, teach concepts, and iterate quickly without context switching.

Overview

PyLiveView executes your active Python file and presents results next to the relevant lines in the editor. It annotates values, highlights errors, and supports common Python patterns including functions, loops, comprehensions, and nested structures.

Features

• Inline value annotations next to the code you’re editing
• Clear error and exception highlighting with line and message details
• Works across functions, loops, comprehensions, and nested objects
• Honors relative imports and project paths
• Optional decorative gutter icons for quick visual scanning

Illustrative examples:

Requirements

• Visual Studio Code ^1.51.0
• Python 3.9+ (tested with 3.10, 3.12)

Installation

Install from VS Code:

1. Open the Extensions view (Ctrl+Shift+X).
2. Search for “PyLiveView”.
3. Install and reload VS Code if prompted.

Alternatively, run from source using the Extension Development Host:

1. Clone or open this repo in VS Code.
2. Press F5 to launch the Extension Development Host.
3. In the new window, open a Python file and run “PyLiveView: Start PyLiveView on the current file”.

Development

• Install dependencies: yarn install
• Build (development): yarn webpack
• Build (watch): yarn webpack-dev or use the typescript: tsc: build - tsconfig.json task
• Lint: yarn lint
• Run tests: yarn test (runs webpack, TypeScript compile, and test harness)
• Launch Extension Dev Host: press F5 in VS Code
• Package VSIX: yarn ext:package

Quick Start

1. Open a Python file in VS Code (e.g., scripts/test.py).
2. Run the command: “PyLiveView: Start PyLiveView on the current file” (pyliveview.runAtCurrentFile).
3. Open the Output panel (View → Output) and select “PyLiveView” to see interpreter info and logs.
4. Edit your code and watch values appear inline. Use “PyLiveView: Stop all running sessions” (pyliveview.stopRunning) to end.

Tips:

• If output looks stale, save the file or restart the session.
• For requests or external APIs, consider caching (e.g., diskcache) to avoid unnecessary calls during iterations.

Commands

• PyLiveView: Start PyLiveView on the current file — pyliveview.runAtCurrentFile
• PyLiveView: Stop all running sessions — pyliveview.stopRunning

Settings

• pyliveview.iconStyleInGutter (boolean, default: true): Toggle decorative gutter icons.
• pyliveview.maxLineLength (number, default: 100): Truncate long inline values.
• pyliveview.updateFrequency (number, default: 500): Minimum time between live updates (ms).
• pyliveview.printLoggingEnabled (boolean, default: true): Show PyLiveView logs in the Output panel.
• pyliveview.pythonPath (string, optional): Path to a Python interpreter (must be 3.9 or greater).

Troubleshooting

• No annotations appearing:

  • Ensure Python 3.9+ is available and configured (see pyliveview.pythonPath).
  • Open the “PyLiveView” Output channel and check for tracer logs or errors.
  • Restart the session: stop then start PyLiveView on the current file.

• Syntax errors:

  • PyLiveView decorates the offending line in red and logs the error message.

• API calls:

  • To avoid unnecessary requests while editing, cache results (e.g., diskcache, Redis) or guard calls.

Acknowledgments

PyLiveView is a modern rebrand and evolution of the original WOLF extension. This rebranding is intended to honor and preserve that foundation while integrating new features, performance improvements, and UX refinements to extend and enhance the original work. We gratefully acknowledge WOLF’s authors and contributors for pioneering live Python code inspection in VS Code.

License

PyLiveView is released under the Apache 2.0 License.

Third-Party Libraries

• Hunter — Flexible code tracing toolkit. (BSD License)

Continuous Publishing (GitHub Actions)

This repository includes a GitHub Actions workflow that will build, run tests, and publish the extension when you push a tag prefixed with v (for example v1.0.0).

Setup steps:

1. Create a Personal Access Token (PAT) with the All accessible organizations and Marketplace publishing scope, or follow the vsce docs for the exact permissions needed.
2. In your GitHub repo, go to Settings → Secrets and variables → Actions and add a secret named VSCE_PAT containing the token.
3. Push a git tag to trigger the workflow:

git tag v1.0.0
git push origin v1.0.0

The workflow .github/workflows/publish.yml will run and publish the extension automatically.