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To prevent a timed-out form submission from creating duplicate work, reuse one idempotency key for every retry of the same operation, bind that key to the request content, and enforce uniqueness in persistent storage. Dirty-state tracking helps decide whether a form needs saving, but it cannot tell you whether a server completed a request whose response was lost.
Why a timeout can still create a duplicate
A timeout tells the client that it did not receive a response in time; it does not establish whether the server received or completed the request. The server may have committed the change just before the connection failed. If the user clicks Submit again and the application treats the second request as new, the operation may happen twice.
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HTTP method semantics matter here. A POST commonly submits data and can cause a state change; repeating it may cause additional effects. An idempotency key is an application-level convention that an API can support to make retries of a particular operation safe. It is not a guarantee supplied automatically by browsers or by every API. MDN Web Docs describes the Idempotency-Key header as experimental and non-standard, so clients must follow the specific endpoint’s documented contract.
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Keep dirty state separate from duplicate protection
Dirty state answers whether the current form differs from a chosen baseline, such as values loaded from the server or values last saved. It can help suppress an unnecessary save, disable a save control when nothing changed, or warn before leaving with unsaved edits. It does not answer whether an earlier request reached the server.
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Choose and maintain the baseline
In React Hook Form, isDirty represents whole-form dirtiness relative to configured default values, while dirtyFields identifies changed fields. These are library state concepts, not universal browser properties. Initialize defaults deliberately and decide when a successful save or refreshed server data should become the new baseline. React Hook Form’s reset options affect which values and state are retained, so background refreshes and post-save resets should be designed rather than assumed.
A pristine form can still be involved in a retry after a lost response; conversely, a dirty form can be submitted more than once. Use dirty state for editing and save UX, and use server-side idempotency for operation reliability.
Give each logical submission one idempotency key
When a user begins a new logical operation, create an opaque key and associate it with that pending operation. Send it with the request in the format the API documents, commonly an Idempotency-Key header. If the response is lost, resend the same operation with the same key and same content. A retry is not a new user intention, so do not generate a fresh key for each network attempt.
Generate a new key for a genuinely new submission. Do not recycle an earlier key after the user changes the form and intends to create a different operation. The API should document key scope, expiration, and what response the client receives when a key is replayed; key retention and replay behavior are not universal.
Separate operation identity from payload identity
The key identifies the logical operation across attempts. A request fingerprint lets the server check that a repeated key is being used with the same relevant request content. Without that check, accidental or malicious reuse of a key with a changed payload can confuse two different intentions.
The server may fingerprint the entire request or selected business-relevant fields. Which fields define the operation, how values are normalized, and how sensitive data is handled are application-specific decisions; there is no universal canonical JSON format or hashing algorithm established by the cited MDN guidance. Treat irrelevant transport details as distinct from the business operation where appropriate, and apply the same normalization consistently before comparing fingerprints.
Make the database arbitrate concurrent requests
An application-side “look up the key, then insert if absent” is not sufficient by itself. Two requests can both observe no existing record before either inserts. Store the key and operation record under a database uniqueness rule that matches the intended scope—for example, account plus key if keys are scoped per account, or an operation type as an additional component where that is part of the design.
PostgreSQL documents that a unique constraint enforces uniqueness across the selected column or columns and creates a unique B-tree index. Use the resulting uniqueness conflict as the durable arbitration point: on conflict, load or return the existing operation according to the API’s replay policy rather than performing the side effect again. The transaction boundary must ensure the record and the operation’s effects cannot leave the system in an ambiguous state; the exact state machine and recovery policy depend on the application.
PostgreSQL treats null values as distinct by default in a unique constraint. A nullable key therefore may allow multiple rows without a key; require a key for operations that need this protection, or deliberately design null handling if keyless records are valid.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Define outcomes for replays and failures
The client and server need a clear contract for each replay situation. A completed operation can return its stored outcome; an operation still running can be reported as in progress; and a reused key with a different fingerprint should be rejected rather than silently treated as the original request. MDN’s examples include missing required key, same key still processing, and key reuse with a different payload, but an API must explicitly implement and document such responses.
| Situation | Recommended handling |
|---|---|
| Same key, same content, operation completed | Return the original result or a documented equivalent without applying the side effect again. |
| Same key, same content, operation in progress | Report an in-progress outcome, such as a documented conflict response, and have the client wait before retrying. |
| Same key, different content | Reject the mismatch. Correct the request or, if it represents a genuinely new operation, use a new key. |
| New user intention | Create a new key and persist it under the same scope and uniqueness rules. |
Document how long keys remain valid and what happens after expiration. Also decide how the system recovers if it records an operation as started but cannot determine whether its side effect completed. These are API and persistence design choices, not properties guaranteed by the header.
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Retry only when the outcome is uncertain or the failure is transient and the endpoint supports idempotency. Keep the same key and request content for each attempt of that operation. Use bounded exponential backoff with random jitter rather than synchronized immediate retries: increasing delays and randomization reduce the chance that many clients will hit a struggling service at once. Stripe’s engineering article discusses failure ambiguity, cached outcomes, retries, and backoff with jitter as general idempotency concerns.
- For a documented in-progress response, wait according to the API contract before trying the same operation again.
- For a payload mismatch, do not keep retrying the unchanged key with changed content; resolve whether the request is a correction or a new operation.
- For an unknown or permanent failure, show a useful status and provide a recovery path instead of retrying indefinitely.
Implementation checklist
- On the client: compare form values with the intended baseline for dirty-state UX; when a new logical submission begins, create and retain one key for that pending operation.
- On each attempt: send the same key and same business-relevant content for retries; generate a different key only for a new user intention.
- On the server: scope the key, compute or otherwise validate the request fingerprint, and document key expiration and replay responses.
- In persistent storage: enforce a uniqueness constraint over the key’s intended scope and handle the conflict by retrieving the existing operation rather than duplicating its effect.
- For recovery: specify how in-progress work, completed replays, mismatches, and uncertain outcomes are represented and resolved.
- For resilience: bound retries and use exponential backoff with jitter for retryable failures.
The important boundary is straightforward: dirty state improves the form’s editing experience; key-plus-fingerprint checks identify safe retries; and a database uniqueness constraint protects against concurrent duplicate processing. Each addresses a different failure mode.
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