Always use proper nullable type annotations and safe access patterns to prevent runtime errors from null/undefined values. Use `Optional[Type]` or `Union[None, Type]` for nullable parameters, employ safe dictionary access with `.get()`, and handle None values explicitly in operations. Examples of good practices: ```python # Use Optional type annotations def process_data(encoder_lens: Optional[torch.Tensor] = None): pass # Safe dictionary access draft_url = params.get("draft_url", None) # Instead of params["draft_url"] # Null-safe assertions assert (topk_weights is None) or (topk_weights.shape == topk_ids_.shape) ``` This prevents KeyError exceptions, improves type safety, and makes null handling explicit rather than implicit. Always consider whether a parameter or variable can be None and handle it appropriately in both type annotations and runtime logic.