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      • Jupyter

      AIO Sandbox includes Jupyter kernel execution for Python code. It is useful for data processing, charts, notebooks, and stateful Python workflows.

      Execute Code

      curl -X POST "http://localhost:8080/v1/jupyter/execute" \
  -H "Content-Type: application/json" \
  -d '{
    "code": "x = 40 + 2\nprint(x)"
  }'

      Stateful Sessions

      Use session_id to keep variables across requests:

      curl -X POST "http://localhost:8080/v1/jupyter/execute" \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "analysis",
    "code": "data = [1, 2, 3]"
  }'

curl -X POST "http://localhost:8080/v1/jupyter/execute" \
  -H "Content-Type: application/json" \
  -d '{
    "session_id": "analysis",
    "code": "print(sum(data))"
  }'

      Kernel Info

      curl "http://localhost:8080/v1/jupyter/info"

      Session Management

      curl "http://localhost:8080/v1/jupyter/sessions"
curl -X DELETE "http://localhost:8080/v1/jupyter/sessions/analysis"

      Tips

      • Use Jupyter for Python code that benefits from stateful variables or rich output.
      • Use /v1/code/execute when you want a language-neutral entry point.
      • Store generated files in the workspace so browser, shell, and file APIs can access them.