A Rust-like result type for Python
Project description
A simple Result type for Python 3 inspired by Rust, fully type annotated.
Installation
Latest release:
$ pip install result
Latest GitHub master branch version:
$ pip install git+https://github.com/rustedpy/result
Summary
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 encapsulating an arbitrary value. Result[T, E] is a generic type alias for typing.Union[Ok[T], Err[E]]. It will change code like this:
def get_user_by_email(email: str) -> Tuple[Optional[User], Optional[str]]:
"""
Return the user instance or an error message.
"""
if not user_exists(email):
return None, 'User does not exist'
if not user_active(email):
return None, 'User is inactive'
user = get_user(email)
return user, None
user, reason = get_user_by_email('ueli@example.com')
if user is None:
raise RuntimeError('Could not fetch user: %s' % reason)
else:
do_something(user)
To something like this:
from result import Ok, Err, Result
def get_user_by_email(email: str) -> Result[User, str]:
"""
Return the user instance or an error message.
"""
if not user_exists(email):
return Err('User does not exist')
if not user_active(email):
return Err('User is inactive')
user = get_user(email)
return Ok(user)
user_result = get_user_by_email(email)
if isinstance(user_result, Ok):
# type(user_result.value) == User
do_something(user_result.value)
else:
# type(user_result.value) == str
raise RuntimeError('Could not fetch user: %s' % user_result.value)
And if you’re using python version 3.10 or later, you can use the elegant match statement as well:
from result import Result, Ok, Err
def divide(a: int, b: int) -> Result[int, str]:
if b == 0:
return Err("Cannot divide by zero")
return Ok(a // b)
values = [(10, 0), (10, 5)]
for a, b in values:
divide_result = divide(a, b)
match divide_result:
case Ok(value):
print(f"{a} // {b} == {value}")
case Err(e):
print(e)
Not all methods (https://doc.rust-lang.org/std/result/enum.Result.html) have been implemented, only the ones that make sense in the Python context. By using isinstance to check for Ok or Err you get type safe access to the contained value when using MyPy to typecheck your code. 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 result import Ok, Err
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
Checking whether a result is Ok or Err. With isinstance you get type safe access that can be checked with MyPy. The is_ok() or is_err() methods can be used if you don’t need the type safety with MyPy:
>>> res = Ok('yay')
>>> isinstance(res, Ok)
True
>>> isinstance(res, Err)
False
>>> res.is_ok()
True
>>> res.is_err()
False
You can also check if an object is Ok or Err by using the OkErr type. Please note that this type is designed purely for convenience, and should not be used for anything else. Using (Ok, Err) also works fine:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> isinstance(res1, OkErr)
True
>>> isinstance(res2, OkErr)
True
>>> isinstance(1, OkErr)
False
>>> isinstance(res1, (Ok, Err))
True
Convert a Result to the value or None:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.ok()
'yay'
>>> res2.ok()
None
Convert a Result to the error or None:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.err()
None
>>> res2.err()
'nay'
Access the value directly, without any other checks:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.value
'yay'
>>> res2.value
'nay'
Note that this is a property, you cannot assign to it. Results are immutable.
For your convenience, simply creating an Ok result without value is the same as using True:
>>> res1 = Ok()
>>> res1.value
True
The unwrap method returns the value if Ok and unwrap_err method returns the error value if Err, otherwise it raises an UnwrapError:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.unwrap()
'yay'
>>> res2.unwrap()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\project\result\result.py", line 107, in unwrap
return self.expect("Called `Result.unwrap()` on an `Err` value")
File "C:\project\result\result.py", line 101, in expect
raise UnwrapError(message)
result.result.UnwrapError: Called `Result.unwrap()` on an `Err` value
>>> res1.unwrap_err()
Traceback (most recent call last):
...
>>>res2.unwrap_err()
'nay'
A custom error message can be displayed instead by using expect and expect_err:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.expect('not ok')
'yay'
>>> res2.expect('not ok')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\project\result\result.py", line 101, in expect
raise UnwrapError(message)
result.result.UnwrapError: not ok
>>> res1.expect_err('not err')
Traceback (most recent call last):
...
>>> res2.expect_err('not err')
'nay'
A default value can be returned instead by using unwrap_or or unwrap_or_else:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.unwrap_or('default')
'yay'
>>> res2.unwrap_or('default')
'default'
>>> res1.unwrap_or_else(str.upper)
'yay'
>>> res2.unwrap_or_else(str.upper)
'NAY'
The unwrap method will raised an UnwrapError. A custom exception can be raised by using the unwrap_or_raise method instead:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.unwrap_or_raise(ValueError)
'yay'
>>> res2.unwrap_or_raise(ValueError)
ValueError: nay
Values and errors can be mapped using map, map_or, map_or_else and map_err:
>>> Ok(1).map(lambda x: x + 1)
Ok(2)
>>> Err('nay').map(lambda x: x + 1)
Err('nay')
>>> Ok(1).map_or(-1, lambda x: x + 1)
2
>>> Err(1).map_or(-1, lambda x: x + 1)
-1
>>> Ok(1).map_or_else(lambda: 3, lambda x: x + 1)
2
>>> Err('nay').map_or_else(lambda: 3, lambda x: x + 1)
3
>>> Ok(1).map_err(lambda x: x + 1)
Ok(1)
>>> Err(1).map_err(lambda x: x + 1)
Err(2)
To save memory, both the Ok and Err classes are ‘slotted’, i.e. they define __slots__. This means assigning arbitrary attributes to instances will raise AttributeError.
The as_result() decorator can be used to quickly turn ‘normal’ functions into Result returning ones by specifying one or more exception types:
@as_result(ValueError, IndexError)
def f(value: int) -> int:
if value == 0:
raise ValueError # becomes Err
elif value == 1:
raise IndexError # becomes Err
elif value == 2:
raise KeyError # raises Exception
else:
return value # becomes Ok
res = f(0) # Err[ValueError()]
res = f(1) # Err[IndexError()]
res = f(2) # raises KeyError
res = f(3) # Ok[3]
Exception (or even BaseException) can be specified to create a ‘catch all’ Result return type. This is effectively the same as try followed by except Exception, which is not considered good practice in most scenarios, and hence this requires explicit opt-in.
Since as_result is a regular decorator, it can be used to wrap existing functions (also from other libraries), albeit with a slightly unconventional syntax (without the usual @):
import third_party
x = third_party.do_something(...) # could raise; who knows?
safe_do_something = as_result(Exception)(third_party.do_something)
res = safe_do_something(...) # Ok(...) or Err(...)
if isinstance(res, Ok):
print(res.value)
FAQ
Why do I get the “Cannot infer type argument” error with MyPy?
There is a bug in MyPy which can be triggered in some scenarios. Using if isinstance(res, Ok) instead of if res.is_ok() will help in some cases. Otherwise using one of these workarounds can help.
License
MIT License
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