Add support for InitVar

[pfrederiks]

Change Summary

dataclasses.InitVar were not handled correctly. This change does the following:

Pass fields typed as InitVar as argument to the original __post_init__ so that they can be processed like in the python 3.7 dataclasses library.

Exclude InitVar fields from the pydantic model as they are not part of the dataclass object.

Related issue number

#592

Checklist

• Unit tests for the changes exist
• Tests pass on CI and coverage remains at 100%
• Documentation reflects the changes where applicable
• HISTORY.rst has been updated
  • if this is the first change since a release, please add a new section
  • include the issue number or this pull request number #<number>
  • include your github username @<whomever>

[codecov]

Codecov Report

Merging #591 into master will not change coverage.
The diff coverage is 100%.

@@          Coverage Diff          @@
##           master   #591   +/-   ##
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  Coverage     100%   100%           
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  Files          15     15           
  Lines        2542   2542           
  Branches      504    504           
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  Hits         2542   2542

[samuelcolvin]

Good start, just need to simplify tests so where possible they test just one thing.

Also need to update HISTORY.rst.

[samuelcolvin]

please also add a test for parameterised InitVar, eg. InitVar[int]

[pfrederiks]

I will test this. The type will be ignored by pydantic though. Init vars are passed to post_init and not part of the model. I could add a type check in pydantic_post_init, but that could turn out to be more complicated than the original fix.

[samuelcolvin]

no need to check the type, we're really just testing that field.type is not dataclasses.InitVar still works (I think it won't, but could be wrong).

[pfrederiks]

field.type is not dataclasses.InitVar still worked, but now I have chosen to use dataclasses.fields instead. This also skips Class variables annotated with typing.ClassVar and it is a public function instead of the private __dataclasses_fields__.

[samuelcolvin]

thanks a lot, much appreciated.