A simple Result type for Python 3 inspired by Rust, fully type annotated.
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('[email protected]')
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.
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()
FalseYou 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))
TrueConvert a Result to the value or None:
>>> res1 = Ok('yay')
>>> res2 = Err('nay')
>>> res1.ok()
'yay'
>>> res2.ok()
NoneConvert 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
TrueThe 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'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)- 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.
MIT License
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