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Claude/ChatGPT Prompt to Migrate Flask from SQLAlchemy 1.x to 2.x

Get a step-by-step plan to migrate a Flask app from SQLAlchemy 1.x to 2.x, with ordered code diffs, typed models, and a risk-aware rollout path.

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What this prompt does

This prompt frames the model as a Python engineer who has migrated production Flask apps from SQLAlchemy 1.x to 2.x, demanding a concrete ordered plan with real code diffs rather than a feature summary. You provide [app_profile], [current_version], [orm_style], and [risk_tolerance], and it returns a staged migration: pre-flight steps, query-API changes, typed mappings, deprecation removal, session/engine adjustments, and verification.

The structure works because ORM major-version jumps hide silent query-behaviour changes, and a big-bang rewrite is risky. [orm_style] tells the model what it's migrating from -- classic Query API versus already-modern usage -- so the diffs are relevant. [risk_tolerance] shapes how aggressive the rollout is, including whether to lean on the legacy compatibility flag. [current_version] and [app_profile] size the effort. Each step pairs before/after diffs with a rollback note, keeping the migration reversible at any point rather than committing you to finish once you start.

When to use it

  • You're moving a Flask app from SQLAlchemy 1.x to 2.x and want a staged, ordered plan.
  • You rely on the classic Query API and need to move to select() and Session.execute().
  • You want typed Mapped[] columns in 2.x declarative mapping.
  • You need to find and remove deprecated patterns before they break.
  • You want each step paired with a code diff and a rollback note, not a summary.
  • You're risk-averse and want to migrate behind the legacy compatibility flag first.
  • You want session/engine and Flask-SQLAlchemy compatibility adjustments handled explicitly.

Example output

You get a numbered migration plan: pin versions and baseline tests, migrate the query API, convert to typed declarative mapping, strip deprecated patterns, fix session/engine and Flask-SQLAlchemy compatibility, then verify with warnings-as-errors. Each step carries before/after code diffs and a rollback note, so it reads as an executable runbook you can work through in order rather than a high-level overview you still have to break into tasks.

Pro tips

  • Describe [orm_style] accurately (Classic Query API with declarative_base) so the diffs match how your code actually queries.
  • Set [current_version] precisely so the legacy-flag and compatibility advice fits your starting point.
  • Match [risk_tolerance] to reality -- low staged migration behind the legacy flag produces a more conservative rollout.
  • Turn deprecation warnings into errors in CI before you start; that surfaces the real work fast.
  • Treat it as a staged migration, never a big-bang rewrite -- the plan is ordered so each step is verifiable on its own.
  • Use the rollback notes; if a step's diff misbehaves on your codebase, you want a defined way back.
  • Convert mappings to typed Mapped[] columns in one pass per model so the diffs stay small and reviewable rather than sprawling across files.

Frequently Asked Questions

Is this a big-bang rewrite or a staged migration?
It is explicitly a staged, ordered migration, never a big-bang rewrite. Each step is verifiable on its own and pairs before/after diffs with a rollback note, so you can move incrementally and revert a single step if it misbehaves on your codebase.
Does it use the legacy compatibility flag?
Yes, the pre-flight step pins versions and enables the legacy compatibility flag, and your `[risk_tolerance]` shapes how much the plan leans on it. A low-risk setting produces a more conservative rollout that stays behind the flag longer before removing deprecated patterns.
How does it handle the Query-to-select() change?
One step migrates the query API from the classic `Query` interface to `select()` and `Session.execute()`. Setting `[orm_style]` accurately matters, since the diffs are tailored to how your code queries today rather than a generic example.
How do I catch leftover deprecated patterns?
The verification step runs with warnings-as-errors to surface anything missed. Turning deprecation warnings into errors in CI before you start is the fastest way to reveal the real scope of work and confirm the migration is complete.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

Engr Mejba Ahmed

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