fix(parser): revert a regression in v3 when raising ValidationError

[leandrodamascena]

Issue number: #5252

Summary

Changes

This PR addresses an issue where we were incorrectly catching and re-raising ValidationError as InvalidModelTypeError. This regression was introduced in v3.0.0

More context:
In v2 we raise ValidationError directly from Pydantic when we can't validate data against model, but in v3 we were catching ValidationError and re-raising it as InvalidModelTypeError. However, ValidationError is a data validation error that many of our customers use to catch exceptions when data is incorrect. By re-raising it as a different error type, we were breaking this expected behavior.

Potential impact:
Any customer that updated to v3 and is relying on InvalidModelTypeError for what were originally ValidationError will need to be updated the code again.

Solution:

• Removed the code that catches ValidationError and re-raises it as InvalidModelTypeError.
• ValidationError will now be raised as is, preserving the original error type and message.
• Created a specific test for this

User experience

Before this PR

from aws_lambda_powertools.utilities.parser import parse, BaseModel, ValidationError
from typing import List, Optional

class OrderItem(BaseModel):
    id: int
    quantity: int
    description: str

class Order(BaseModel):
    id: int
    description: str
    items: List[OrderItem] # nesting models are supported
    optional_field: Optional[str] = None # this field may or may not be available when parsing


payload = {
    "id": 10876546789,
    "description": "My order",
    "items": [
        {
            # this will cause a validation error
            "id": [1015938732],
            "quantity": 1,
            "description": "item xpto"
        }
    ]
}

def my_function():
    try:
        parsed_payload: Order = parse(event=payload, model=Order)
        # payload dict is now parsed into our model
        return parsed_payload.items
    except ValidationError:
        return {
            "status_code": 400,
            "message": "Invalid order"
        }

/home/john/.pyenv/versions/sftp-processor-3.12/lib/python3.12/site-packages/aws_lambda_powertools/package_logger.py:20: UserWarning: POWERTOOLS_DEBUG environment variable is enabled. Setting logging level to DEBUG.
  if powertools_debug_is_set():
2024-09-26 16:07:09,201 aws_lambda_powertools.utilities.parser.parser [DEBUG] Parsing and validating event model; no envelope used
Traceback (most recent call last):
  File "/home/john/.pyenv/versions/sftp-processor-3.12/lib/python3.12/site-packages/aws_lambda_powertools/utilities/parser/parser.py", line 195, in parse
    return adapter.validate_python(event)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/.pyenv/versions/sftp-processor-3.12/lib/python3.12/site-packages/pydantic/type_adapter.py", line 135, in wrapped
    return func(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/.pyenv/versions/sftp-processor-3.12/lib/python3.12/site-packages/pydantic/type_adapter.py", line 366, in validate_python
    return self.validator.validate_python(object, strict=strict, from_attributes=from_attributes, context=context)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
pydantic_core._pydantic_core.ValidationError: 1 validation error for Order
items.0.id
  Input should be a valid integer [type=int_type, input_value=[1015938732], input_type=list]
    For further information visit https://errors.pydantic.dev/2.9/v/int_type

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/john/sandbox/sftp-processor/sftp-request-processor/sftp_request_model.py", line 260, in <module>
    parsed_payload: Order = parse(event=payload, model=Order)
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/.pyenv/versions/sftp-processor-3.12/lib/python3.12/site-packages/aws_lambda_powertools/utilities/parser/parser.py", line 203, in parse
    raise InvalidModelTypeError(
aws_lambda_powertools.utilities.parser.exceptions.InvalidModelTypeError: Error: 1 validation error for Order
items.0.id
  Input should be a valid integer [type=int_type, input_value=[1015938732], input_type=list]
    For further information visit https://errors.pydantic.dev/2.9/v/int_type. Please ensure the Input model inherits from BaseModel,
and your payload adheres to the specified Input model structure.
Model=<class '__main__.Order'>

After this PR

Customers can catch ValidationError as expected.

{'status_code': 400, 'message': 'Invalid order'}

Checklist

If your change doesn't seem to apply, please leave them unchecked.

• Meet tenets criteria
• I have performed a self-review of this change
• Changes have been tested
• Changes are documented
• PR title follows conventional commit semantics

Is this a breaking change?

RFC issue number:

Checklist:

• Migration process documented
• Implement warnings (if it can live side by side)

Acknowledgment

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Disclaimer: We value your time and bandwidth. As such, any pull requests created on non-triaged issues might not be successful.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 96.20%. Comparing base (72b9546) to head (da03498).
Report is 1 commits behind head on develop.

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #5259      +/-   ##
===========================================
- Coverage    96.21%   96.20%   -0.01%     
===========================================
  Files          229      229              
  Lines        10753    10753              
  Branches      2002     2002              
===========================================
- Hits         10346    10345       -1     
- Misses         321      322       +1     
  Partials        86       86              

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[dreamorosi]

Thank you for fixing this, as discussed earlier today let's treat this as a regression and call out the fix in the release notes.

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarCloud