Release Date: July 2025

Feature Status: Performance Enhancement

Breaking Changes: None

Feature Summary

HyperFlow's Python execution environment now uses lazy loading for heavy data science libraries (numpy, pandas, matplotlib, scipy, PIL). This reduces memory usage and startup time for simple Python scripts while maintaining full compatibility with existing code.

What's New

Lazy Loading Architecture

Heavy libraries are now loaded only when explicitly imported by user code:

• Immediate loading: Lightweight libraries (json, requests, datetime, etc.)
• On-demand loading: Data science libraries (numpy, pandas, matplotlib, scipy, PIL)
• Zero code changes: All existing Python scripts continue to work unchanged

Performance Improvements

• Memory reduction: 50-80MB less memory usage for simple scripts
• Faster startup: 200-500ms quicker initialization for lightweight operations
• Better scaling: More concurrent Python nodes possible

User Impact

No changes required - all existing Python code works exactly the same:

# These still work - just load when first imported
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from PIL import Image

# These are still pre-loaded
import json
import requests

Known Changes

1. First import latency: Heavy libraries may add 100-200ms delay on first use