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What You’ll Learn

  • Writing data files into a sandbox with sbx.files.write()
  • Writing executable Python scripts into a sandbox
  • Running scripts with sbx.commands.run()
  • Reading generated output files back with sbx.files.read()
  • End-to-end data pipeline inside an isolated sandbox

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Prerequisites

This example is available in Python. TypeScript version coming soon.

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Code Walkthrough

Upload the CSV dataset directly as a string — no disk I/O on the host: 
from declaw import Sandbox

sbx = Sandbox.create(template="python", timeout=300)
try:
    csv_data = """name,age,city,salary
Alice,30,New York,85000
Bob,25,San Francisco,92000
Charlie,35,Chicago,78000
Diana,28,Boston,95000
Eve,32,Seattle,88000"""
    sbx.files.write("/tmp/data.csv", csv_data)
    print("Wrote /tmp/data.csv")
Upload the analysis script as a multiline Python string: 
    analysis_script = '''
import csv
import json

with open("/tmp/data.csv") as f:
    reader = csv.DictReader(f)
    rows = list(reader)

results = {
    "total_records": len(rows),
    "avg_age": sum(int(r["age"]) for r in rows) / len(rows),
    "avg_salary": sum(int(r["salary"]) for r in rows) / len(rows),
    "cities": list(set(r["city"] for r in rows)),
    "highest_salary": max(rows, key=lambda r: int(r["salary"]))["name"],
}

with open("/tmp/results.json", "w") as f:
    json.dump(results, f, indent=2)

print(json.dumps(results, indent=2))
'''
    sbx.files.write("/tmp/analyze.py", analysis_script)
    print("Wrote /tmp/analyze.py")
Run the analysis and capture stdout: 
    result = sbx.commands.run("python3 /tmp/analyze.py")
    print(f"stdout:\n{result.stdout}")
Read back the generated results file: 
    results_content = sbx.files.read("/tmp/results.json")
    print(f"results.json:\n{results_content}")
finally:
    sbx.kill()
This pattern works for any file format — JSON, Parquet, images, or binary data. sbx.files.write() accepts both string and bytes content.

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Expected Output

==================================================
Declaw Upload Dataset & Analyze Example
==================================================

--- Creating Sandbox ---
Sandbox created: sbx_abc123

--- Uploading CSV Dataset ---
Wrote /tmp/data.csv

--- Uploading Analysis Script ---
Wrote /tmp/analyze.py

--- Running Analysis ---
stdout:
{
  "total_records": 5,
  "avg_age": 30.0,
  "avg_salary": 87600.0,
  "cities": ["New York", "San Francisco", "Chicago", "Boston", "Seattle"],
  "highest_salary": "Diana"
}

--- Reading Results File ---
results.json:
{
  "total_records": 5,
  "avg_age": 30.0,
  "avg_salary": 87600.0,
  "cities": ["New York", "San Francisco", "Chicago", "Boston", "Seattle"],
  "highest_salary": "Diana"
}

--- Cleaning Up ---
Sandbox killed.

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Done!
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