Bug: data masking prepare_data leaves dataclasses and Pydantic models unconverted

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@therealemmanueloppong 已经在做这个了。

开始于 2026年11月1日。

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Issue 类型
缺陷
描述清晰度
描述清楚
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活跃
技术栈
python
领域
backend

调研方向

Start with prepare_data in aws_lambda_powertools.utilities.data_masking.base and inspect how _visited is updated during recursive conversion. Run the reproduction in the issue and the existing circular-reference test, then add regression coverage in tests/functional/data_masking/_pydantic/test_data_masking_with_pydantic.py. Done means repeated dataclass and Pydantic instances are converted while circular references remain detected.

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描述

Expected Behaviour

DataMasking.erase (and the other operations that go through prepare_data) should convert every dataclass and Pydantic model in the input to plain data, however many there are and whether or not the same instance appears twice.

Current Behaviour

prepare_data records the id() of every object it has visited in _visited to detect circular references, and never removes them. That includes the temporary dicts built by dataclasses.asdict() and model_dump(). Once one of those is freed, CPython reuses its id for a later object, which is then taken for a circular reference and returned unconverted. An instance referenced twice is skipped the same way. erase then fails with TypeError: Object of type X is not JSON serializable.

Code snippet
from dataclasses import dataclass
from pydantic import BaseModel
from aws_lambda_powertools.utilities.data_masking import DataMasking
from aws_lambda_powertools.utilities.data_masking.base import prepare_data

class Card(BaseModel):
    number: str

@dataclass
class Item:
    card: Card

print(prepare_data({"items": [Item(Card(number=str(i))) for i in range(5)]}))
# some items still contain Card(...) objects instead of dicts

@dataclass
class Person:
    age: int

p = Person(age=30)
DataMasking().erase({"items": [p, p]}, fields=["items[*].age"])
# TypeError: Object of type Person is not JSON serializable
Possible Solution

Keep in _visited only the objects on the current conversion path (add before recursing, remove in a finally). Circular references are still caught, and the existing circular-reference test still passes. I have this fix with regression tests in tests/functional/data_masking/_pydantic/test_data_masking_with_pydantic.py (fail on develop, pass with the change) and can open a PR once this is triaged.

Steps to Reproduce

Run the snippet above on develop (5785377).

Powertools for AWS Lambda (Python) version

latest (3.37.0, develop)

AWS Lambda function runtime

3.13

Packaging format used

PyPi

Debugging logs
N/A
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Python
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环境准备

从这里开始

  1. 先读完整个 Issue，再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库，在一个分支上完成修改。
  4. 提交 Pull Request，并在描述里引用这个 Issue 编号。

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