Use date/time/datetime Python types

[twwd]

according to the OpenAPI property type for all output model types

Fixes #1615

[codecov]

Codecov Report

All modified lines are covered by tests ✅

Comparison is base (e9b6edf) 100.00% compared to head (52c2bd1) 100.00%.
Report is 740 commits behind head on master.

Additional details and impacted files

@@             Coverage Diff             @@
##            master     #1618     +/-   ##
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  Coverage   100.00%   100.00%             
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  Files           11        34     +23     
  Lines         1020      3755   +2735     
  Branches       201       879    +678     
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+ Hits          1020      3755   +2735     

Flag	Coverage Δ
unittests	99.65% <99.60%> (?)

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Files	Coverage Δ
datamodel_code_generator/__init__.py	100.00% <100.00%> (ø)
datamodel_code_generator/__main__.py	100.00% <100.00%> (ø)
datamodel_code_generator/arguments.py	100.00% <100.00%> (ø)
datamodel_code_generator/format.py	100.00% <100.00%> (ø)
datamodel_code_generator/http.py	100.00% <100.00%> (ø)
datamodel_code_generator/imports.py	100.00% <100.00%> (ø)
datamodel_code_generator/model/__init__.py	100.00% <100.00%> (ø)
datamodel_code_generator/model/base.py	100.00% <100.00%> (ø)
datamodel_code_generator/model/dataclass.py	100.00% <100.00%> (ø)
datamodel_code_generator/model/enum.py	100.00% <100.00%> (ø)
... and 24 more

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[twwd]

It might be better to set the type to datetime.time etc. instead of just time etc. to prevent naming clashes.

[koxudaxi]

@twwd
Thank you for creating this PR.
In pydantic, parsing allows normal strings to be cast to datetime.datetime, but this is not done in dataclass or typedDict. Considering that OpenAPI is used as an interface definition with outside Python, wouldn't this change no longer match the use cases for dataclass or TypedDict? There will probably be a need to cast from string to datetime.datetime before assigning it to a dataclass.

[twwd]

I parse the server JSON response into a dataclass and handle the type conversion but I see that this is not the general use-case.
I patch the method as a workaround (if somebody else has a similar use-case)

with mock.patch('datamodel_code_generator.model.types.type_map_factory') as type_map_factory_mock:
   type_map_factory_mock.side_effect = adjusted_type_map_factory