Comments (3)
As you've noticed, cattrs will deal with the field before it reaches attrs and attrs will apply the converter. This can't be changed for a number of reasons like backwards-compatibility and the fact it interferes with other uses of attrs converters.
The immediate fix would be to make a converter with prefer_attrib_converters=True
and use it.
c = cattrs.Converter(prefer_attrib_converters=True)
print(Foo(2.0))
print(Foo("None"))
print(c.structure({"a": 2.0}, Foo))
print(c.structure({"a": "None"}, Foo))
But I think a better approach would be to remove the attrs converter and have cattrs deal with this. That way the rest of your code base can be isolated from the details of data structuring, which is one of the points of cattrs.
Like this:
import attrs
import cattrs
from cattrs.gen import make_dict_structure_fn
def converter(x: str | float | None, _) -> float | None:
if x is None or x == "None":
return None
return float(x)
@attrs.define
class Foo:
a: float | None
c = cattrs.Converter()
c.register_structure_hook(
Foo, make_dict_structure_fn(Foo, c, a=cattrs.override(struct_hook=converter))
)
print(c.structure({"a": 2.0}, Foo))
print(c.structure({"a": "None"}, Foo))
Let me know what you think! I'm going to close this in the meantime.
from cattrs.
Thank you very much for your insight!
I agree that it's better to isolate the nuances of the data format, and a custom Converter is the right tool for that. I was just coming at the problem from the wrong angle.
from cattrs.
Another solution using newtypes: you can register the hook just once for that newtype, instead of for every field in every class:
ParsedFloat = typing.NewType("ParsedFloat", float)
@attrs.define
class Foo:
a: ParsedFloat | None = None
def converter(x: str | float | None, _) -> ParsedFloat | None:
if x is None or x == "None":
return None
return ParsedFloat(float(x))
c = cattrs.Converter()
c.register_structure_hook(ParsedFloat, converter)
The signature of the converter is a little unorthodox, and this still leaks parsing information into the class definition. In this case I think it's a worthy tradeoff:
-
I am parsing a complex structure with a lot of classes and a lot of fields to clean up in this way. The newtype approach is more maintainable compared to listing the classes+fields in two different places (the class definition and converter creation)
-
The classes (
Foo
in this example) are specifically only used for ingesting data, it's not used by the main application. The output will be aggregated with data from other sources in a separate data structure that is used by the application.
from cattrs.
Related Issues (20)
- Constructor selection for structuring HOT 7
- Tagged Union: How to do structure/unstructure hook(s) for particular member type? HOT 4
- A dictionary gets structured into a list without errors/warnings HOT 2
- Question: Correct use of converters HOT 3
- Documentation does not explain unstruct_collection_overrides' input HOT 4
- Detailed validation exception groups with hook errors HOT 2
- cattrs effectively disables attrs validation HOT 3
- Covert to defaultdict instead of plain dict HOT 4
- How to recursively unstructure with hooks? HOT 5
- Dataclass structuring fails with misleading error message.
- [macOS] Error when trying to run tests: `ImportError: cannot import name 'CodecOptions' from 'bson'` HOT 2
- How to hook into structuring of a simple dict? HOT 6
- Incorrect dispatch in Python 3.12 HOT 4
- Why does structuring of datetime in attrs class need a structure hook? HOT 1
- `prefer_attrib_converters` doesn't work when the field is aliased HOT 2
- Register structure hook only for optional types HOT 2
- TYPE_CHECKING and init=False HOT 5
- Problem with tagged union example HOT 3
- Subclass disambiguation for nested structures. HOT 3
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from cattrs.