Mailman 3 dataclass allow_missing option - Python-ideas

17 Dec 2020


      Hi all,
Dataclasses provide a unique way of creating parameter bags with decent
typing and validation options. However, they currently lack a meaningful
way of detecting a missing value as a dataclass interface consumer.
Current behavior allows us to specify defaults per property, but defining a
default value has consequences for the reusability of the dataclass,
especially when it comes to inheritance patterns. Aside from this effect,
littering the code with `str_field: str = MISSING_STR` does not really
provide a clean and readable interface.
Therefore, I would like to propose an extra option on both the
dataclasses.dataclass decorator as well as a dataclasses.field boolean
argument called `allow_missing`.
Example:
@dataclass(allow_missing=True)
class UserBag:
  user_id: UUID
bag = UserBag() # no exception with regards to missing args
bag.user_id # type: Missing[UUID] ?
if not bag.user_id: # sentinel value evaluates to false
  ...
if dataclasses.ismissing(bag.user_id): # or more explicit
  ...
Alternatively, as api on a per-field-basis:
@dataclass
class UserBag:
  user_id: UUID = field(allow_missing=True)
As a bonus, one would imagine the `asdict` method has an argument to
convert a dataclass instance to a dictionary without the missing properties
(example: `asdict(d, exclude_missing=True)`).
Generation of code could stay largely the same as it currently is, with
only minor differences:
- type hinting of constructor args should provide a sentinel default value
that adheres to the typing of the original field, something along the lines
of `__init__(self, arg = Missing[str])`
- exception currently raised if a Missing[T] value is detected after
construction should be silenced if the field is marked as missable.
- current sentinel MISSING value evaluates to True when cast as boolean
I would love to have your feedback on this.
Best,
Eelke van den Bos