In this time of Daytona SDK teaching, we provide handbox's Preda-Dayton-Dayton's Dayton-Dayton's Sandon National Natural Dayton. Since the construction of the exact Sandbox and the performance of the basic code, the guide shows how to divide processes, enter dependent, and run simple texts without risking local environment. As a tutorial progresses, it passes to data in pandas, file functioning including learning and writing on JSON files, and making complicated snippets such as mature tasks and filing algoriths. Finally, it shows the murder of all sand boxes and relevant cleaning procedures, to ensure that all service is managed and false.
import os
import time
import json
from typing import List, Dict, Any
try:
import daytona_sdk
except ImportError:
print("Installing Daytona SDK...")
!pip install daytona-sdk
import daytona_sdk
from daytona_sdk import Daytona, DaytonaConfig, CreateSandboxParamsWe include and import DayTona SDK (if not already), then start Core Daytona (Daytonaconfig, and DaytonAconBOxpronparams) to prepare and build Python Sandvol boxes safe. It also brought familiar items such as OS, time, and JSON for use within those sandboxs.
class DaytonaTutorial:
"""Complete tutorial for Daytona SDK - Secure AI Code Execution Platform"""
def __init__(self, api_key: str):
"""Initialize Daytona client"""
self.config = DaytonaConfig(api_key=api_key)
self.daytona = Daytona(self.config)
self.sandboxes: List[Any] = []
def basic_sandbox_demo(self):
"""Demo 1: Basic sandbox creation and code execution"""
print("🚀 Demo 1: Basic Sandbox Operations")
print("-" * 40)
try:
sandbox = self.daytona.create(CreateSandboxParams(language="python"))
self.sandboxes.append(sandbox)
print(f"✅ Created sandbox: {sandbox.id}")
code="print("Hello from Daytona Sandbox!")nprint(f"2 + 2 = {2 + 2}")"
response = sandbox.process.code_run(code)
if response.exit_code == 0:
print(f"📝 Output: {response.result}")
else:
print(f"❌ Error: {response.result}")
except Exception as e:
print(f"❌ Error in basic demo: {e}")
def data_processing_demo(self):
"""Demo 2: Data processing in isolated environment"""
print("n📊 Demo 2: Secure Data Processing")
print("-" * 40)
try:
sandbox = self.daytona.create(CreateSandboxParams(language="python"))
self.sandboxes.append(sandbox)
install_cmd = "import subprocess; subprocess.run(['pip', 'install', 'pandas'])"
response = sandbox.process.code_run(install_cmd)
data_code = """
import pandas as pd
import json
# Create sample dataset
data = {
'name': ['Alice', 'Bob', 'Charlie', 'Diana'],
'age': [25, 30, 35, 28],
'salary': [50000, 60000, 70000, 55000]
}
df = pd.DataFrame(data)
result = {
'total_records': len(df),
'avg_age': df['age'].mean(),
'avg_salary': df['salary'].mean(),
'summary': df.describe().to_dict()
}
print(json.dumps(result, indent=2))
"""
response = sandbox.process.code_run(data_code)
if response.exit_code == 0:
print("✅ Data processing completed:")
print(response.result)
else:
print(f"❌ Error: {response.result}")
except Exception as e:
print(f"❌ Error in data processing demo: {e}")
def file_operations_demo(self):
"""Demo 3: File operations within sandbox"""
print("n📁 Demo 3: File Operations")
print("-" * 40)
try:
sandbox = self.daytona.create(CreateSandboxParams(language="python"))
self.sandboxes.append(sandbox)
file_code = """
import os
import json
# Create a sample file
data = {'message': 'Hello from Daytona!', 'timestamp': '2025-06-13'}
with open('sample.json', 'w') as f:
json.dump(data, f, indent=2)
# Read and display file contents
with open('sample.json', 'r') as f:
content = f.read()
print("File contents:")
print(content)
# List files in current directory
files = os.listdir('.')
print(f"\nFiles in directory: {files}")
"""
response = sandbox.process.code_run(file_code)
if response.exit_code == 0:
print("✅ File operations completed:")
print(response.result)
else:
print(f"❌ Error: {response.result}")
except Exception as e:
print(f"❌ Error in file operations demo: {e}")
def ai_code_execution_demo(self):
"""Demo 4: Simulated AI-generated code execution"""
print("n🤖 Demo 4: AI-Generated Code Execution")
print("-" * 40)
ai_codes = [
"# Calculate fibonacci sequencendef fib(n):n if n <= 1: return nn return fib(n-1) + fib(n-2)nprint([fib(i) for i in range(10)])",
"# Sort algorithmndef bubble_sort(arr):n n = len(arr)n for i in range(n):n for j in range(0, n-i-1):n if arr[j] > arr[j+1]:n arr[j], arr[j+1] = arr[j+1], arr[j]n return arrnprint(bubble_sort([64, 34, 25, 12, 22, 11, 90]))",
"# Data analysisnimport mathndata = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]nmean = sum(data) / len(data)nvariance = sum((x - mean) ** 2 for x in data) / len(data)nstd_dev = math.sqrt(variance)nprint(f'Mean: {mean}, Std Dev: {std_dev:.2f}')"
]
try:
sandbox = self.daytona.create(CreateSandboxParams(language="python"))
self.sandboxes.append(sandbox)
for i, code in enumerate(ai_codes, 1):
print(f"n🔄 Executing AI Code Snippet {i}:")
response = sandbox.process.code_run(code)
if response.exit_code == 0:
print(f"✅ Output: {response.result}")
else:
print(f"❌ Error: {response.result}")
time.sleep(1)
except Exception as e:
print(f"❌ Error in AI code execution demo: {e}")
def parallel_execution_demo(self):
"""Demo 5: Multiple sandboxes for parallel processing"""
print("n⚡ Demo 5: Parallel Execution")
print("-" * 40)
tasks = [
"print('Task 1: Computing prime numbers')nprimes = [i for i in range(2, 50) if all(i % j != 0 for j in range(2, int(i**0.5) + 1))]nprint(f'Primes: {primes[:10]}')",
"print('Task 2: String processing')ntext="Hello Daytona World"nprint(f'Reversed: {text[::-1]}')nprint(f'Word count: {len(text.split())}')",
"print('Task 3: Mathematical calculations')nimport mathnresult = sum(math.sqrt(i) for i in range(1, 101))nprint(f'Sum of square roots 1-100: {result:.2f}')"
]
try:
parallel_sandboxes = []
for i in range(len(tasks)):
sandbox = self.daytona.create(CreateSandboxParams(language="python"))
parallel_sandboxes.append(sandbox)
self.sandboxes.append(sandbox)
results = []
for i, (sandbox, task) in enumerate(zip(parallel_sandboxes, tasks)):
print(f"n🏃 Starting parallel task {i+1}")
response = sandbox.process.code_run(task)
results.append((i+1, response))
for task_num, response in results:
if response.exit_code == 0:
print(f"✅ Task {task_num} completed: {response.result}")
else:
print(f"❌ Task {task_num} failed: {response.result}")
except Exception as e:
print(f"❌ Error in parallel execution demo: {e}")
def cleanup_sandboxes(self):
"""Clean up all created sandboxes"""
print("n🧹 Cleaning up sandboxes...")
print("-" * 40)
for sandbox in self.sandboxes:
try:
self.daytona.remove(sandbox)
print(f"✅ Removed sandbox: {sandbox.id}")
except Exception as e:
print(f"❌ Error removing sandbox {sandbox.id}: {e}")
self.sandboxes.clear()
print("🎉 Cleanup completed!")
def run_full_tutorial(self):
"""Run the complete Daytona tutorial"""
print("🎯 Daytona SDK Complete Tutorial")
print("=" * 50)
print("Secure & Isolated AI Code Execution Platform")
print("=" * 50)
self.basic_sandbox_demo()
self.data_processing_demo()
self.file_operations_demo()
self.ai_code_execution_demo()
self.parallel_execution_demo()
self.cleanup_sandboxes()
print("n🎊 Tutorial completed successfully!")
print("Key Daytona features demonstrated:")
print("• Secure sandbox creation")
print("• Isolated code execution")
print("• File system operations")
print("• Parallel processing")
print("• Resource cleanup")This DayTonatuotial Category includes the full guide for the end of the Daytona SDK client: It starts a safe sandbox repair with data pandas), and eventually certified by multiple resources. Each method contains good features, showcasing keytona Features, creating a Sandbox box, Safe Substance, Safe Execution, Clear Works Stairs to run in writing.
def main():
"""Main function to run the tutorial"""
print("🔑 Daytona Setup Instructions:")
print("1. Visit:
print("2. Create an account")
print("3. Generate API key at:
print("4. Replace 'YOUR_API_KEY' below with your actual key")
print("-" * 50)
API_KEY = "Use Your API Key Here"
if API_KEY == "YOUR_API_KEY":
print("⚠️ Please set your Daytona API key before running the tutorial!")
print(" Update the API_KEY variable with your key from
return
try:
tutorial = DaytonaTutorial(API_KEY)
tutorial.run_full_tutorial()
except Exception as e:
print(f"❌ Tutorial failed: {e}")
print("💡 Make sure your API key is valid and you have network access")The main function () describes the initial setup steps, directing users to create a DayTona account and generate their API key, and confirm that the key is given before traveling by DayTotouTorial Class and fully moving. If the API key is lost or not valid, printing clearest orders and ACHORTS, verifying the original period.
if __name__ == "__main__":
main()
Finally, the above checkpiece of the Python-Point Check above confirms that () is only deteriorated when the text is headed straight, starting the Daytona's work.
In conclusion, in terms of this lesson, enhancements have access to the complete understanding of the largest skills of unity: creating protective python deceiving, manufacturing loads of opposing work or produced, and maintaining strong management system. Cleaning routes emphasizes the importance of the performance of resources in a long-term service delivery. It equipped with these basic skills, users can combine with confidence in the Daytona Day with a large machine, automated test structures, any condition that requires safe code.
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