prime-sandboxes 0.2.4

Prime Intellect Sandboxes SDK - Manage remote code execution environments

Prime Sandboxes SDK

Lightweight Python SDK for managing Prime Intellect sandboxes - secure remote code execution environments.

Features

• Synchronous and async clients - Use with sync or async/await code
• Full sandbox lifecycle - Create, list, execute commands, upload/download files, delete
• Type-safe - Full type hints and Pydantic models
• Authentication caching - Automatic token management
• Bulk operations - Create and manage multiple sandboxes efficiently
• No CLI dependencies - Pure SDK, ~50KB installed

Installation

uv pip install prime-sandboxes

Or with pip:

pip install prime-sandboxes

Quick Start

from prime_sandboxes import APIClient, SandboxClient, CreateSandboxRequest

# Initialize
client = APIClient(api_key="your-api-key")
sandbox_client = SandboxClient(client)

# Create a sandbox
request = CreateSandboxRequest(
    name="my-sandbox",
    docker_image="python:3.11-slim",
    cpu_cores=2,
    memory_gb=4,
)

sandbox = sandbox_client.create(request)
print(f"Created: {sandbox.id}")

# Wait for it to be ready
sandbox_client.wait_for_creation(sandbox.id)

# Execute commands
result = sandbox_client.execute_command(sandbox.id, "python --version")
print(result.stdout)

# Clean up
sandbox_client.delete(sandbox.id)

Async Usage

import asyncio
from prime_sandboxes import AsyncSandboxClient, CreateSandboxRequest

async def main():
    async with AsyncSandboxClient(api_key="your-api-key") as client:
        # Create sandbox
        sandbox = await client.create(CreateSandboxRequest(
            name="async-sandbox",
            docker_image="python:3.11-slim",
        ))

        # Wait and execute
        await client.wait_for_creation(sandbox.id)
        result = await client.execute_command(sandbox.id, "echo 'Hello from async!'")
        print(result.stdout)

        # Clean up
        await client.delete(sandbox.id)

asyncio.run(main())

Authentication

The SDK looks for credentials in this order:

1. Direct parameter: APIClient(api_key="sk-...")
2. Environment variable: export PRIME_API_KEY="sk-..."
3. Config file: ~/.prime/config.json (created by prime login CLI command)

Advanced Features

File Operations

# Upload a file
sandbox_client.upload_file(
    sandbox_id=sandbox.id,
    file_path="/app/script.py",
    local_file_path="./local_script.py"
)

# Download a file
sandbox_client.download_file(
    sandbox_id=sandbox.id,
    file_path="/app/output.txt",
    local_file_path="./output.txt"
)

Bulk Operations

# Create multiple sandboxes
sandbox_ids = []
for i in range(5):
    sandbox = sandbox_client.create(CreateSandboxRequest(
        name=f"sandbox-{i}",
        docker_image="python:3.11-slim",
    ))
    sandbox_ids.append(sandbox.id)

# Wait for all to be ready
statuses = sandbox_client.bulk_wait_for_creation(sandbox_ids)

# Delete by IDs or labels
sandbox_client.bulk_delete(sandbox_ids=sandbox_ids)
# OR by labels
sandbox_client.bulk_delete(labels=["experiment-1"])

Labels & Filtering

# Create with labels
sandbox = sandbox_client.create(CreateSandboxRequest(
    name="labeled-sandbox",
    docker_image="python:3.11-slim",
    labels=["experiment", "ml-training"],
))

# List with filters
sandboxes = sandbox_client.list(
    status="RUNNING",
    labels=["experiment"],
    page=1,
    per_page=50,
)

for s in sandboxes.sandboxes:
    print(f"{s.name}: {s.status}")

Documentation

Full API reference: https://github.com/PrimeIntellect-ai/prime-cli/tree/main/packages/prime-sandboxes

Related Packages

• prime - Full CLI + SDK with pods, inference, and more (includes this package)

License

MIT License - see LICENSE file for details