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Installation

Basic Installation​

Install Code Sandboxes using pip:

pip install code-sandboxes

Optional Dependencies​

Code Sandboxes supports different execution backends via extras:

# With Datalayer variant support
pip install code-sandboxes[datalayer]

# With Docker variant support
pip install code-sandboxes[docker]

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

# With Google Colab support
pip install code-sandboxes[colab]

# With Monty (secure in-process interpreter) support
pip install code-sandboxes[monty]

# With Modal variant support
pip install code-sandboxes[modal]

# All features
pip install code-sandboxes[all]

Requirements​

  • Python 3.10 or higher
  • For Docker variant: Docker installed and running
  • For Datalayer variant: valid DATALAYER_API_KEY
  • For Kaggle variant: code-sandboxes[kaggle] and Kaggle credentials (for batch mode) or runtime connection values (for interactive mode)
  • For Google Colab variant: code-sandboxes[colab] and a Colab runtime assignment (server URL, kernel id, proxy token)
  • For Monty variant: code-sandboxes[monty] (no credentials required)
  • For Modal variant: code-sandboxes[modal] and Modal credentials (modal token new or MODAL_TOKEN_ID / MODAL_TOKEN_SECRET)

Configuration​

Environment Variables​

VariableDescription
DATALAYER_API_KEYAPI key for Datalayer runtime authentication
DATALAYER_RUN_URLCustom Datalayer service URL (optional)
MODAL_TOKEN_IDModal token id (Modal variant)
MODAL_TOKEN_SECRETModal token secret (Modal variant)

Programmatic Configuration​

from code_sandboxes import Sandbox, SandboxConfig

config = SandboxConfig(
    timeout=30.0,
    environment="python-cpu-env",
    memory_limit=4 * 1024**3,  # 4GB
    cpu_limit=2.0,
    working_dir="/workspace",
    env_vars={"DEBUG": "1"},
)

sandbox = Sandbox.create(config=config)

Verifying Installation​

from code_sandboxes import Sandbox

with Sandbox.create() as sandbox:
    result = sandbox.run_code("print('Installation successful!')")
    print(result.stdout)