Question 1

How do I convert a function that raises exceptions to use Result in Option?

Accepted Answer

Wrap the function in a try/except block that returns Ok on success and Err on exception. For example, define a wrapper that catches exceptions and maps them to Err values, ensuring the function signature returns a Result type.

Question 2

What's the difference between Option and Python's built-in Optional type?

Accepted Answer

Option is a sum type with Some and NONE variants that forces explicit handling via methods like map or unwrap, while Optional is a type hint that doesn't enforce handling and can still lead to None errors if ignored. Option adds runtime safety through its API.

Question 3

Is Option library compatible with async/await for error handling?

Accepted Answer

Yes, you can use Option and Result in async functions by wrapping async calls in Result types, but you may need to handle async-specific errors manually, as the library doesn't provide built-in async adapters out of the box.

Question 4

How to chain multiple operations with Option or Result without nested checks?

Accepted Answer

Use methods like map, and_then, or flat_map to compose operations. For example, result.map(lambda x: x * 2).and_then(another_function) chains success paths and propagates errors automatically, reducing boilerplate.

Question 5

Can I use Option with mypy or other type checkers effectively?

Accepted Answer

Yes, since Option is fully typed with Python's type hints, mypy can validate usage, but you may need to ensure your type annotations are precise, especially with generics like Result[dict, int] from the quick start example.

Question 6

What are the performance impacts of using __slots__ in this library?

Accepted Answer

__slots__ reduce memory usage by preventing the creation of __dict__ for instances, which can improve performance in memory-intensive applications, but the overhead of object creation for Option/Result might still be higher than using raw values in some cases.

Question 7

Option vs other Python functional libraries like returns: which is better?

Accepted Answer

Option is simpler and focused on Rust-like Option/Result with slot optimization, while returns offers more advanced functional features. Choose Option for a lightweight, type-safe approach, or returns if you need richer monadic operations and ecosystem tools.

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