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v0.4.2: Comprehensive Error Handling

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@Routhleck Routhleck released this 24 Aug 01:58
· 50 commits to master since this release
v0.4.2
684f2ab

🛡️ Major Error Handling Improvements

This release completely eliminates crashes and provides robust error handling for invalid inputs.

🎯 Key Fixes

  • No more crashes: Eliminated "Fatal Python error: Aborted" when using invalid parameters
  • Proper exceptions: Rust errors now convert to Python ValueError exceptions
  • Input validation: Comprehensive validation for modulus, NaN values, and matrix formats
  • System stability: Errors don't crash the Python interpreter

✨ Error Handling Features

Non-Prime Modulus Handling

# Before: CRASH with "Fatal Python error: Aborted"
# After: Proper exception
try:
    result = canns_ripser.ripser(points, coeff=4)  # 4 is not prime
except ValueError as e:
    print(f"Error: {e}")  # "Modulus must be prime..."

NaN Input Validation

  • NaN values in distance matrices are detected and raise clear error messages
  • Sparse matrices with NaN values are properly validated
  • Invalid matrix dimensions are caught gracefully

System Recovery

  • After encountering an error, the system continues working normally
  • No need to restart Python interpreter after invalid inputs

🔧 Technical Improvements

  • Result-based error handling: All Rust functions use Result<T, String> types
  • Error propagation: Proper error chains from Rust to Python
  • Input validation: Comprehensive validation at all entry points
  • Zero panics: Eliminated all panic!() calls in favor of recoverable errors

📊 Compatibility & Performance

  • ✅ Full backward compatibility: No breaking changes to API
  • ✅ Zero performance impact: Error handling only activates on invalid inputs
  • ✅ Maintains all optimizations: Performance improvements from v0.4.0/v0.4.1 retained

🧪 Testing

  • Added comprehensive error handling test suite
  • Verified error recovery and system stability
  • All existing functionality tests continue to pass

🏆 User Benefits

  • Better developer experience: Clear error messages instead of cryptic crashes
  • Production stability: Applications can handle errors gracefully
  • Debugging friendly: Proper Python stack traces for all error conditions
  • Pythonic interface: Follows Python exception handling conventions

This release makes CANNS-Ripser much more robust and user-friendly while maintaining its high-performance characteristics.

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