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Migrating Stored Data without Domain Corruption

Page Maps

graph LR
  family["Python Programming"]
  program["Python Object-Oriented Programming"]
  section["Persistence Serialization Schema Evolution"]
  page["Migrating Stored Data without Domain Corruption"]
  capstone["Capstone evidence"]

  family --> program --> section --> page
  page -.applies in.-> capstone
flowchart LR
  orient["Orient on the page map"] --> read["Read the main claim and examples"]
  read --> inspect["Inspect the related code, proof, or capstone surface"]
  inspect --> verify["Run or review the verification path"]
  verify --> apply["Apply the idea back to the module and capstone"]

Read the first diagram as a placement map: this page is one concept inside its parent module, not a detached essay, and the capstone is the pressure test for whether the idea holds. Read the second diagram as the working rhythm for the page: name the problem, study the example, identify the boundary, then carry one review question forward.

Purpose

Plan data migration so stored artifacts can evolve without normalizing broken history into the live domain.

1. Migration Is a Domain Risk

Bad migration code can do more harm than bad schema code because it rewrites the past. Treat migration scripts as production code with explicit review and verification.

2. Prefer Repeatable, Observable Steps

Strong migration plans answer:

  • what transforms
  • how it is verified
  • whether it can run twice safely
  • how to recover if it stops halfway

That is more important than compressing everything into one clever script.

3. Keep Repair Logic Separate from Everyday Loading

Do not let normal repositories absorb one-off migration behavior forever. Use explicit migration tools when possible, and keep runtime loaders focused on supported versions.

4. Validate Semantics after Shape Change

A migration that produces syntactically valid data can still violate domain meaning. Re-run domain construction, contract tests, or sample audits after transformation.

Practical Guidelines

  • Treat migration code as reviewed, tested production code.
  • Design migrations to be observable, restartable, and preferably idempotent.
  • Keep one-off repair logic out of normal repository paths when practical.
  • Verify semantic validity after migration, not only structural validity.

Exercises for Mastery

  1. Write a migration checklist for one stored format in your system.
  2. Add a semantic validation step after a shape-changing migration.
  3. Identify one migration behavior that should not remain in the normal load path.