{ } 📦 Code Sandboxes

Code Sandboxes (code_sandboxes) is a Python package for running code in isolated sandbox variants through a unified API.

Canonical variant names:

datalayer
docker
eval
google_colab
jupyter
kaggle
modal
monty

Documentation

The full documentation is the single source of truth:

Docs home: https://code-sandboxes.datalayer.tech
Sandboxes and variant setup: https://code-sandboxes.datalayer.tech/sandboxes
Installation: https://code-sandboxes.datalayer.tech/installation
CLI usage: https://code-sandboxes.datalayer.tech/cli
API reference: https://code-sandboxes.datalayer.tech/api-reference
Examples: https://code-sandboxes.datalayer.tech/examples
Comparison: https://code-sandboxes.datalayer.tech/comparison

Published site:

https://code-sandboxes.datalayer.tech

Install

pip install code-sandboxes

For backend-specific extras and credentials, see https://code-sandboxes.datalayer.tech/installation and https://code-sandboxes.datalayer.tech/sandboxes.

Jupyter Sandbox

from code_sandboxes import Sandbox

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

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

Kaggle Sandbox

Kaggle supports both batch execution and interactive connections through the kaggle sandbox. Install its optional dependency first:

pip install "code-sandboxes[kaggle]"

Required credentials for batch mode:

~/.kaggle/kaggle.json, or
KAGGLE_API_KEY

# Install Kaggle support
pip install code-sandboxes[kaggle]

# Optional: env-based credentials (if not using ~/.kaggle/kaggle.json)
export KAGGLE_API_KEY="<your-kaggle-api-key>"

# Launch the REPL
sandbox repl --variant kaggle

For batch execution, configure Kaggle credentials and create the sandbox without a runtime URL:

from code_sandboxes import Sandbox

with Sandbox.create(variant="kaggle") as sandbox:
    result = sandbox.run_code("print('hello from kaggle')")
    print(result.stdout)

The lower-level batch API is also available directly:

from code_sandboxes import KaggleKernelExecutor

executor = KaggleKernelExecutor()
result = executor.execute(
    "print('hello from kaggle')",
    title="code-sandboxes-demo",
    accelerator="NvidiaTeslaT4",
    wait=True,
)
print(result.status, result.stdout)
print(result.to_kernel_reply())

For interactive execution, copy the WebSocket channels URL from an active Kaggle notebook session and pass it to the sandbox or client:

from code_sandboxes import KaggleKernelClient

with KaggleKernelClient.from_channels_url(channels_url, token=None) as kernel:
    print(kernel.execute("x = 1 + 1; print(x)"))

See the complete Kaggle guide for authentication, accelerators, channels URL retrieval, and execution options.

Google Colab

Google Colab exposes an already-running kernel through an authenticating proxy. Copy its WebSocket channels URL from the browser's Network tools, then pass it directly to the sandbox:

from code_sandboxes import Sandbox

with Sandbox.create(variant="google_colab", channels_url=channels_url) as sandbox:
    print(sandbox.run_code("x = 1 + 1; print(x)").stdout)

The lower-level client and parser are owned by Code Sandboxes as well:

from code_sandboxes import GoogleColabKernelClient, parse_google_colab_channels_url

server_url, kernel_id, proxy_token = parse_google_colab_channels_url(channels_url)
with GoogleColabKernelClient.from_channels_url(channels_url) as kernel:
    print(kernel.execute("print('hello from colab')"))

See the complete Google Colab guide for proxy authentication, explicit connection values, and channels URL retrieval.

License

BSD 3-Clause License

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

code_sandboxes-1.0.8-py3-none-any.whl (82.6 kB view details)

Uploaded Aug 15, 2026 Python 3

File details

Details for the file code_sandboxes-1.0.8-py3-none-any.whl.

File metadata

Download URL: code_sandboxes-1.0.8-py3-none-any.whl
Upload date: Aug 15, 2026
Size: 82.6 kB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: twine/7.0.0 CPython/3.13.11

File hashes

Hashes for code_sandboxes-1.0.8-py3-none-any.whl
Algorithm	Hash digest
SHA256	`efcc2b2fd85cb0d85f325a744f0f903d7259835454cb40f6e6a6f1a911359074`
MD5	`41f218f239473a63709f45e009fab4c1`
BLAKE2b-256	`a482dbca43ed9f75e9552fcfeccd3ab28a9bd8d37f9918f3b4c2f0d4ee936eb4`