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Level 6 / Project 11 - Dead Letter Row Handler

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Focus

  • bad row pipeline and quarantine

Why this project exists

This project gives you level-appropriate practice in a realistic operations context. Goal: run the baseline, alter behavior, break one assumption, recover safely, and explain the fix.

Run (copy/paste)

Use <repo-root> as the folder containing this repository's README.md.

cd <repo-root>/projects/level-6/11-dead-letter-row-handler
python project.py --input data/sample_input.txt --output data/output_summary.json
pytest -q

Expected terminal output

{
  "input_records": 6,
  "processed": 3,
  "dead_lettered": 3,
  "dead_letter_stats": {"total": 3, "unresolved": 3, "resolved": 0}
}

Expected artifacts

  • data/output_summary.json — processing results with dead-letter details
  • Passing tests (pytest -q → 6+ passed)
  • Updated notes.md

Alter it (required)

  1. Add a --max-retries flag: dead-letter rows with retry_count >= max should be marked as permanently failed.
  2. Add a retry_all CLI command that re-runs validation on every unresolved dead-letter row.
  3. Add a reason_summary that counts how many dead-letters failed for each error type.
  4. Re-run script and tests after each change.

Break it (required)

  1. Process a record with value: null and observe the error path.
  2. Retry a dead-letter row that still has the same validation issue — confirm retry_count increments.
  3. Delete the dead_letters table mid-run and observe the crash.

Fix it (required)

  1. Handle null values explicitly in validate_record.
  2. Add a --create-tables flag that ensures tables exist before processing (idempotent).
  3. Add a test for the retry-increment behavior.

Explain it (teach-back)

  1. What is a dead-letter queue, and where does the name come from?
  2. Why store the original payload alongside the error, instead of just logging?
  3. When should dead-letter rows be retried vs. permanently discarded?
  4. How does this pattern apply to message queues like RabbitMQ or SQS?

Mastery check

You can move on when you can: - run baseline without docs, - explain one core function line-by-line, - break and recover in one session, - keep tests passing after your change.

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