AI Code Runner Sandbox
Pricing
from $0.39 / 1,000 code executions
Run JavaScript or Python code in an isolated sandbox. Pass data via stdin, capture stdout and stderr, parse JSON output, save generated files, and get one structured execution record with a wall timeout and output caps.
You can access the AI Code Runner Sandbox programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
1from apify_client import ApifyClient2
3# Initialize the ApifyClient with your Apify API token4# Replace '<YOUR_API_TOKEN>' with your token.5client = ApifyClient("<YOUR_API_TOKEN>")6
7# Prepare the Actor input8run_input = {9 "language": "javascript",10 "code": """const chunks = [];11for await (const chunk of process.stdin) chunks.push(chunk);12const input = JSON.parse(Buffer.concat(chunks).toString() || '{}');13console.log(JSON.stringify({ sum: input.values.reduce((a, b) => a + b, 0), count: input.values.length }));""",14 "stdin": """{15 \"values\": [3, 5, 8]16}""",17 "timeoutSeconds": 5,18 "maxOutputBytes": 256000,19 "saveFiles": [],20 "maxSavedFileBytes": 5000000,21}22
23# Run the Actor and wait for it to finish24run = client.actor("parsebird/code-runner-sandbox").call(run_input=run_input)25
26# Fetch and print Actor results from the run's dataset (if there are any)27print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")28for item in client.dataset(run.default_dataset_id).iterate_items():29 print(item)30
31# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startThe Apify API client for Python is the official library that allows you to use AI Code Runner Sandbox API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: