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Jupyter

Runs code against a local or remote Jupyter Server and connects through its Jupyter kernel client. This variant provides process isolation via the Jupyter kernel and persistent state across requests.

  • Requirements: jupyter_server and jupyter-kernel-client (included by default).
  • Parameters: server_url, token, host/port (when the sandbox starts its own server), python_executable.

How To Obtain The Token​

  • If you start the server yourself, you choose the token: 
    jupyter server --port 8888 --IdentityProvider.token MY_TOKEN
  • For an already-running server, list servers and read the token=... value: 
    jupyter server list
    # http://localhost:8888/?token=abcd1234...  :: /home/you/notebooks
    You can also pass the full http://host:port/?token=... URL as server_url; the token is parsed automatically.
  • If you omit server_url, JupyterSandbox starts and manages its own local Jupyter Server and generates the token for you — no configuration needed.

Usage​

from code_sandboxes import Sandbox

# Connect to an existing server:
with Sandbox.create(
    variant="jupyter",
    server_url="http://localhost:8888",
    token="MY_TOKEN",
) as sandbox:
    sandbox.run_code("x = 40")
    result = sandbox.run_code("x + 2")
    print(result.text)  # 42

# Or let the sandbox manage a local server automatically:
with Sandbox.create(variant="jupyter") as sandbox:
    print(sandbox.run_code("1 + 1").text)  # 2

The concrete implementation is available from a top-level module:

from code_sandboxes.jupyter_sandbox import JupyterSandbox