DM-37214: Fix problem with JSON formatter when Pydantic is used but Dict requested #761
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Now that read storage class being different to write storage class no longer directly means that a component is being used, the logic in FileFormatter to extract a component has to change. 1. The extraction must happen from the original python type that was written and not the, possibly, generic python type read from disk. This requires we do a coercion before extracting the component. 2. Built-in types must always be converted to the original storage class before conversion to the requested read storage class. 3. Remove duplicate logic from JSON and YAML that was trying to convert built-in types to the requested type. This now has moved to the parent class.
Codecov ReportBase: 85.32% // Head: 85.37% // Increases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## main #761 +/- ##
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+ Coverage 85.32% 85.37% +0.05%
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Files 260 261 +1
Lines 34560 34605 +45
Branches 5819 5816 -3
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+ Hits 29488 29544 +56
+ Misses 3826 3818 -8
+ Partials 1246 1243 -3
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TallJimbo
approved these changes
Dec 8, 2022
Remove the requirement that we only do this if we did not write it originally as a built-in type -- it didn't really affect the code because of the presence of the isinstance check later on (which has now moved into the main check).
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Test that we can round trip Pydantic models, dataclasses, classes that get created from dicts, and tuples using JSON and YAML formatters.
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JSON natively reads
dictand so was never triggering the conversion code to the proper internal type before converting that to a dict. ForTaskMetadatathis could lead to oddities because the dict view ofTaskMetadatadoes not match the internal model layout.Checklist
doc/changes