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A rust-like result type for Python

Project description

Resultify

This is an opinionated, simplified fork of dbrgn/result.

Result is a simple, type annotated Result type for Python 3.6+ inspired by Rust.

The idea is that a result value can be either Ok(value) or Err(error), with a way to differentiate between the two. Ok and Err are both classes wrapping an arbitrary value. Result[T, E] is a generic type alias for typing.Union[Ok[T], Err[E]].

Requires Python 3.6 or higher!

Caveats

Not all methods have been implemented, only the ones that make sense in the Python context. For example, the map methods have been omitted, because they don't quite make sense without Rust's pattern matching.

Since Rust's Optional type does not meaningfully translate to Python in a way type checkers are able to understand, ok() corresponds to unwrap() and err() corresponds to unwrap_err(). On the other side, you don't have to return semantically unclear tuples anymore.

By using .is_ok() and is_err() to check for Ok or Err you get type safe access to the contained value. All of this in a package allowing easier handling of values that can be OK or not, without resorting to custom exceptions.

API

Creating an instance:

>>> from resultify import Ok, Err
>>> ok = Ok('yay')
>>> res2 = Err('nay')

Type safe checking whether a result is Ok or Err.

>>> res = Ok('yay')
>>> res.is_ok()
True
>>> res.is_err()
False

Unwrap a Result, or raise if trying to extract a result from an error from a result or vice-versa:

>>> ok = Ok('yay')
>>> err = Err('nay')
>>> ok.ok()
'yay'
>>> ok.err()
resultify.UnwrapError: Cannot unwrap error from Ok: Ok('yay')
>>> err.err()
'nay'
>>> err.ok()
resultify.UnwrapError: Cannot unwrap value from Err: Err('nay')

For your convenience, and to appease the type checkers, simply creating an Ok result without value is the same as using True:

>>> ok = Ok()
>>> ok.ok()
True

To easily convert a function to return Result, you can use resultify():

>>> from resultify import resultify
>>> @resultify()
... def a():
...     return "value"
...
>>> a()
Ok('value')

You can similarly auto-capture exceptions using resultify(...). Please note that you can provide multiple exceptions, or none if you don't want to catch the exception! This is primarily useful when modeling code paths with a single good branch and multiple early raises, where one does not have to concern oneself with annoying try ... catch ... statements.

>>> @resultify(TypeError)
... def foo():
...     raise TypeError()
...
>>> foo()
Err(TypeError())

You can retry a function that returns a Result type with a constant backoff.

>>> from resultify import resultify, retry
... @retry(retries=2, delay=2, initial_delay=1):
... @resultify(Exception)
... def foo():
...     # do something that needs retrying here

This example waits 1 second before executing the initial call, then attempts the initial call, then executes two retries, spaces out two seconds from the previous call. If any execution was a success, the Ok value will be returned. If the retries were exhausted and no Ok was returned, we return the Err value.

For those running Python 3.10, you can make use of Python's structural pattern matching like this:

>>> from resultify import Ok, Err
>>> ok = Ok("ok!")
>>> match ok:
...     case Ok(foo): print(f"Yay {foo}")
...     case Err(foo): print(f"Nay {foo}")
...
Yay ok!
>>> no = Err("nope!")
>>> match no:
...     case Ok(foo): print(f"Yay {foo}")
...     case Err(foo): print(f"Nay {foo}")
...
Nay nope!

Since documentation always lies, please refer to the unit tests for examples of usage.

License

MIT License

Project details


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