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"""Demo script to test Modal code execution integration.
Run with: uv run python examples/modal_demo/test_code_execution.py
"""
import sys
from pathlib import Path
# Add src to path
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
from src.tools.code_execution import CodeExecutionError, get_code_executor
def test_basic_execution():
"""Test basic code execution."""
print("\n=== Test 1: Basic Execution ===")
executor = get_code_executor()
code = """
print("Hello from Modal sandbox!")
result = 2 + 2
print(f"2 + 2 = {result}")
"""
result = executor.execute(code)
print(f"Success: {result['success']}")
print(f"Stdout:\n{result['stdout']}")
if result["stderr"]:
print(f"Stderr:\n{result['stderr']}")
def test_scientific_computing():
"""Test scientific computing libraries."""
print("\n=== Test 2: Scientific Computing ===")
executor = get_code_executor()
code = """
import pandas as pd
import numpy as np
# Create sample data
data = {
'drug': ['DrugA', 'DrugB', 'DrugC'],
'efficacy': [0.75, 0.82, 0.68],
'sample_size': [100, 150, 120]
}
df = pd.DataFrame(data)
# Calculate weighted average
weighted_avg = np.average(df['efficacy'], weights=df['sample_size'])
print(f"Drugs tested: {len(df)}")
print(f"Weighted average efficacy: {weighted_avg:.3f}")
print("\\nDataFrame:")
print(df.to_string())
"""
result = executor.execute(code)
print(f"Success: {result['success']}")
print(f"Output:\n{result['stdout']}")
def test_statistical_analysis():
"""Test statistical analysis."""
print("\n=== Test 3: Statistical Analysis ===")
executor = get_code_executor()
code = """
import numpy as np
from scipy import stats
# Simulate two treatment groups
np.random.seed(42)
control_group = np.random.normal(100, 15, 50)
treatment_group = np.random.normal(110, 15, 50)
# Perform t-test
t_stat, p_value = stats.ttest_ind(treatment_group, control_group)
print(f"Control mean: {np.mean(control_group):.2f}")
print(f"Treatment mean: {np.mean(treatment_group):.2f}")
print(f"T-statistic: {t_stat:.3f}")
print(f"P-value: {p_value:.4f}")
if p_value < 0.05:
print("Result: Statistically significant difference")
else:
print("Result: No significant difference")
"""
result = executor.execute(code)
print(f"Success: {result['success']}")
print(f"Output:\n{result['stdout']}")
def test_with_return_value():
"""Test execute_with_return method."""
print("\n=== Test 4: Return Value ===")
executor = get_code_executor()
code = """
import numpy as np
# Calculate something
data = np.array([1, 2, 3, 4, 5])
result = {
'mean': float(np.mean(data)),
'std': float(np.std(data)),
'sum': int(np.sum(data))
}
"""
try:
result = executor.execute_with_return(code)
print(f"Returned result: {result}")
print(f"Mean: {result['mean']}")
print(f"Std: {result['std']}")
print(f"Sum: {result['sum']}")
except CodeExecutionError as e:
print(f"Error: {e}")
def test_error_handling():
"""Test error handling."""
print("\n=== Test 5: Error Handling ===")
executor = get_code_executor()
code = """
# This will fail
x = 1 / 0
"""
result = executor.execute(code)
print(f"Success: {result['success']}")
print(f"Error: {result['error']}")
def main():
"""Run all tests."""
print("=" * 60)
print("Modal Code Execution Demo")
print("=" * 60)
tests = [
test_basic_execution,
test_scientific_computing,
test_statistical_analysis,
test_with_return_value,
test_error_handling,
]
for test in tests:
try:
test()
except Exception as e:
print(f"\n❌ Test failed: {e}")
import traceback
traceback.print_exc()
print("\n" + "=" * 60)
print("Demo completed!")
print("=" * 60)
if __name__ == "__main__":
main()
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