fix: add checking type of 'result' (#626) #730
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* (fix): add checking type of 'result' in '._add_result_to_memory()' method * (fix): add checking that 'result' dict contains 'type' and 'value' the keys in '._add_result_to_memory()' method
WalkthroughThe recent changes to the pandasai/smart_datalake package primarily focus on enhancing the input validation in the In addition, the Changes
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pandasai/smart_datalake/__init__.py
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| f"Both 'type' and 'value' items should be present in 'result' " | ||
| f"produced by generated code. Instead it contains the next " | ||
| f"content:\n{result}" | ||
| ) |
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Great catch. I'm not entirely sure this is the place to do this check.
What if before we run self._add_result_to_memory(result) on line 508, we execute another method self._validate_result and in there we:
- check if both type and value are present
- check if the type is one of the ones accepted
If any of the conditions is not true, we raise an error.
What do you think? @nautics889
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Thanks for the review, @gventuri.
You're right, there is another validation a little bit before, therefore on the 508'th line we likely can operate validation_ok. So, as turns out, the current PR brings an excessive validation for containing "type" and "value". I've already noticed that before actually, but as seemed to me, it requires a bit of refactoring.
Working on it...
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Yes, great catch! Fortunately we are now working on simplifying the process a little bit. Too many things happen now and we need to improve the way we separate responsibilities.
* (refactor): update 'SmartDataframe' * (fix): remove an excessive validation in '_add_result_to_memory()' method due to duplicating of the functionality * (chore): rename 'validation_ok' to 'result_is_valid' * (fix): add pre-defining for 'result_is_valid' * (refactor): simplify conditions checking
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## main #730 +/- ##
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+ Coverage 85.25% 85.65% +0.39%
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Files 73 73
Lines 3574 3575 +1
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+ Hits 3047 3062 +15
+ Misses 527 513 -14
... and 3 files with indirect coverage changes 📣 Codecov offers a browser extension for seamless coverage viewing on GitHub. Try it in Chrome or Firefox today! |
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Apologies for the delay. @gventuri i'd be glad if you check the current update. At first i'd like to highlight that i was trying to not change processing logic (behaviour) at all, since this is supposed to be a minor update. So that's why a call to To summarize, the latest commit contains the next points:
Exuse me for the large diff. |
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Actionable comments generated: 1
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Files selected for processing (1)
- pandasai/smart_datalake/init.py (4 hunks)
Additional comments: 2
pandasai/smart_datalake/__init__.py (2)
- 466-492: > Note: This review was outside of the patch, so it was mapped to the patch with the greatest overlap. Original lines [366-514]
The changes introduce a validation step for the result object, which is a good practice to ensure the integrity of the data before it is used or stored. The use of a separate
result_is_validflag to control the flow is clear and effective. However, it's important to ensure that theoutput_type_helper.validatemethod is thoroughly tested, especially since it's handling dynamic input. Additionally, the logging of validation failures is crucial for debugging and should be maintained.
- 530-535: The
_add_result_to_memorymethod now includes a check for the type of result before adding it to memory. This is a good practice to ensure that only expected types of results are stored. However, it's important to ensure that all possible valid types are accounted for and that the method gracefully handles any unexpected types that may be encountered.
| if result_is_valid: | ||
| self._add_result_to_memory(result) | ||
| else: | ||
| self.logger.log( | ||
| "The result will not be memorized since it has failed the " | ||
| "corresponding validation" | ||
| ) |
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The conditional check for result_is_valid before adding the result to memory is a good practice to prevent storing invalid or unexpected data. However, it would be beneficial to ensure that there is a mechanism to handle the situation where results are consistently invalid, such as alerting an administrator or triggering a deeper investigation into the cause of the validation failures.
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@nautics889 thanks a lot for the refactor, as always 🚀! Merging it! |
This PR adds an additional verification in
_add_result_to_memory()ofSmartDatalake.Ensure that
resultis actually a dictionary.Ensure that
resultcontains"type"and"value"the items.Summary by CodeRabbit