# Token is available as environment variable
echo $JUPYTER_TOKEN

# Use in requests:
curl -sf "http://localhost:8888/api/status?token=$JUPYTER_TOKEN" | jq .

curl -sf "http://localhost:8888/api/kernels?token=$JUPYTER_TOKEN" | jq .

curl -sf -X POST "http://localhost:8888/api/kernels?token=$JUPYTER_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"name": "python3"}' | jq .
# → {"id": "<kernel-id>", "name": "python3", "state": "starting", ...}

curl -sf -X POST "http://localhost:8888/api/kernels/<kernel-id>/restart?token=$JUPYTER_TOKEN" | jq .

curl -sf -X DELETE "http://localhost:8888/api/kernels/<kernel-id>?token=$JUPYTER_TOKEN"

curl -sf "http://localhost:8888/api/contents/notebooks?token=$JUPYTER_TOKEN" | jq '.content[] | {name, path, type}'

curl -sf -X PUT "http://localhost:8888/api/contents/notebooks/analysis.ipynb?token=$JUPYTER_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "notebook",
    "content": {
      "cells": [
        {
          "cell_type": "markdown",
          "source": "# Analysis Notebook\nCreated by Prismer Academic Assistant.",
          "metadata": {}
        },
        {
          "cell_type": "code",
          "source": "import numpy as np\nimport matplotlib.pyplot as plt\nprint(\"Ready!\")",
          "metadata": {},
          "outputs": [],
          "execution_count": null
        }
      ],
      "metadata": {
        "kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
        "language_info": {"name": "python", "version": "3.12.3"}
      },
      "nbformat": 4,
      "nbformat_minor": 5
    }
  }' | jq '{name, path, created}'

curl -sf "http://localhost:8888/api/contents/notebooks/analysis.ipynb?token=$JUPYTER_TOKEN" | jq .

curl -sf -X DELETE "http://localhost:8888/api/contents/notebooks/analysis.ipynb?token=$JUPYTER_TOKEN"

# Write a cell's code to temp file and execute
cat > /tmp/cell.py << 'PYTHON'
import numpy as np
x = np.random.randn(1000)
print(f"Mean: {x.mean():.4f}, Std: {x.std():.4f}")
PYTHON

python3 /tmp/cell.py

# 1. Start kernel
KERNEL_ID=$(curl -sf -X POST "http://localhost:8888/api/kernels?token=$JUPYTER_TOKEN" \
  -H "Content-Type: application/json" -d '{"name":"python3"}' | jq -r '.id')

# 2. Execute code via the kernel (uses WebSocket internally)
# For simple cases, write the notebook with cells and outputs.
# For complex interactive sessions, guide the user to open Jupyter in browser.