Standard-Labs / real-intent

Python SDK and abstracted interface for BigDBM's API.
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Approximation of equivalent PII objects #35

Closed preritdas closed 2 months ago

preritdas commented 2 months ago

Closes #32.

Allowing the removal of humans believed to already be in a set of leads, despite having different MD5s.

Summary by CodeRabbit

coderabbitai[bot] commented 2 months ago

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Commits Files that changed from the base of the PR and between 99241bddaf475091020d8e59f9a4ed9842e9508d and ce9f4f4f481ccc4e35f6785d713bc2bcca2ad9c8.

Walkthrough

Recent changes enhance the functionality and integrity of the bigdbm application by introducing a custom equality method in the PII class for meaningful comparisons, and a new SamePersonValidator class to eliminate duplicate representations of individuals based on MD5 hashes. These updates promote better identity verification and data deduplication while maintaining the overall structure of existing models.

Changes

Files Change Summary
bigdbm/schemas.py Added __eq__ method in PII class for custom equality comparisons; reordered fields for better logical grouping.
bigdbm/validate/simple.py Introduced SamePersonValidator class to filter out duplicate MD5 hashes, enhancing data integrity during validation.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant Validator
    participant PII

    User->>Validator: Submit list of MD5 hashes
    Validator->>Validator: Initialize unique_leads list
    loop Check each MD5
        Validator->>Validator: Compare MD5 with unique_leads
        alt MD5 not found
            Validator->>Validator: Add MD5 to unique_leads
        end
    end
    Validator->>User: Return unique MD5 list

🐇 In the world of data, where numbers reside,
The rabbit hops in, with wisdom as guide.
With equality found, and duplicates gone,
Our PII blooms bright like the dawn!
Hooray for the changes, so clever and neat,
In the garden of data, we dance on our feet! 🌼✨


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