Data Subject Request (DSR) Reference Number Regex for Python

What this pattern does

This page provides a well-structured, multi-part regular expression for matching data subject request (dsr) reference number, ported and verified for Python. Identity and credential patterns need both correctness and safety, since they're frequent targets for adversarial input. The snippet below is ready to drop into your Python project — whether you're validating in a Django view, a FastAPI endpoint, or a standalone data processing script.

Python Implementation

# Data Subject Request (DSR) Reference Number
# ReDoS-safe | RegexVault — Identity & PII > Consent & Compliance

import re

data_subject_request_dsr_reference_number_pattern = re.compile(r'^(?:DSR|DSAR|SAR|RTF|RTE|REC)[\-][0-9]{4}[\-][0-9]{4,8}$')

def validate_data_subject_request_dsr_reference_number(value: str) -> bool:
    return bool(data_subject_request_dsr_reference_number_pattern.fullmatch(value))

# Example
print(validate_data_subject_request_dsr_reference_number("DSR-2024-00001234"))  # True

Test Cases

When to use this pattern

This pattern is drawn from the Identity & PII > Consent & Compliance category and carries a ReDoS-safe certification. That matters for Python developers because particularly important in Python web servers where CPU-bound regex operations can stall concurrent request handling. RegexVault audits patterns against known backtracking attack vectors, ensuring you have the necessary context before using this regex in a high-stakes production environment.

Common Pitfalls

Technical Notes

DSR reference formats: DSR=Data Subject Request, DSAR=Data Subject Access Request, SAR=Subject Access Request (UK), RTF=Right to Forget, RTE=Right to Erasure, REC=Rectification. Year prefix allows filtering by year. Sequential number ensures uniqueness.