Pydantic: Forbid floats on integer fields?

[MrMrRobat]

Question, Suggestion

Now if you pass float to int field, it will be converted to int without any error or warning. That could cause some unexpected behavior.

import pydantic

class MyModel(pydantic.BaseModel):
    a: int

m = MyModel(a=3.4)
print(m.a)  # 3

What I would expect to happen is:

m = MyModel(a=3.4)

Traceback (most recent call last):
    ...
pydantic.error_wrappers.ValidationError: 1 validation error
a
  value is not a valid integer (type=type_error.integer)

[dmontagu]

There is a note addressing this in the new docs:

Data Conversion

pydantic may cast input data to force it to conform model field types. This may result in data being lost, take the following example:

from pydantic import BaseModel

class Model(BaseModel):
    a: int
    b: float
    c: str

print(Model(a=3.1415, b=' 2.72 ', c=123).dict())
#> {'a': 3, 'b': 2.72, 'c': '123'}

(This script is complete, it should run "as is")

This is a deliberate decision of pydantic, and in general it's the most useful approach, see here for a longer discussion of the subject.

[dmontagu]

Also, there is a StrictInt type in pydantic.types (at least that's what it's called in v1, not sure if/where it exists in 0.32.2) that can be used to prevent floats if that's what you want.

[MrMrRobat]

Thanks for quick reply and solution! Checked for StrictInt earlier without luck, will look for it in current versions.

[dmontagu]

It may not exist in 0.32.2 at all -- but you can probably copy the code as a workaround until v1 is released!