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This guide walks you through creating a sandbox, checking its status, and tearing it down.

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Prerequisites

  • Python 3.9+
  • Tensorlake SDK installed: pip install tensorlake

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Create a Sandbox

from tensorlake.sandbox import SandboxClient

client = SandboxClient()

# Create a sandbox with a Python image
sandbox = client.create(
    image="python:3.11-slim",
    cpus=1.0,
    memory_mb=512,
    ephemeral_disk_mb=1024,
    timeout_secs=300
)

print(f"Sandbox ID: {sandbox.sandbox_id}")
print(f"Status: {sandbox.status}")  # "Pending" or "Running"

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Check Sandbox Status

info = client.get(sandbox.sandbox_id)
print(f"Status: {info.status}")
print(f"Image: {info.image}")
print(f"Resources: {info.resources.cpus} CPUs, {info.resources.memory_mb} MB RAM")

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List All Sandboxes

sandboxes = client.list()
for sb in sandboxes:
    print(f"{sb.sandbox_id}: {sb.status}")

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Tear Down a Sandbox

client.delete(sandbox.sandbox_id)
print("Sandbox terminated")

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Full Example

from tensorlake.sandbox import SandboxClient

with SandboxClient() as client:
    # Create
    sandbox = client.create(
        image="python:3.11-slim",
        cpus=2.0,
        memory_mb=1024,
        ephemeral_disk_mb=2048,
        timeout_secs=600,
        allow_internet_access=False  # No network access
    )

    sandbox_id = sandbox.sandbox_id
    print(f"Created sandbox: {sandbox_id}")

    # Check status
    info = client.get(sandbox_id)
    print(f"Status: {info.status}")

    # Tear down
    client.delete(sandbox_id)
    print("Sandbox terminated")

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Next Steps

Lifecycle

Sandbox states, resources, and timeouts.

Networking

Control network access.

Pools

Pre-warm containers for faster creation.