What techniques can be used to persist and restore form validation state across reloads in a ClojureScript application?
0 reputation · 15 Oct 2025, 14:11 UTC
0 reputation · 15 Oct 2025, 14:11 UTC
Persisting form validation state in a ClojureScript frontend requires capturing the current validation data, storing it durably across reloads, and restoring it so users see the same error messages and field statuses after navigation.
Key considerations include identifying where validation results are held (e.g., an atom or Re‑frame db slice), choosing a serialization format compatible with client‑side storage, deciding on a storage mechanism that respects size limits, and arranging automatic updates when the validation map changes.
How should the validation map be identified within an atom or Re‑frame db? What storage mechanism (localStorage, sessionStorage, IndexedDB) offers the best trade‑off between capacity and persistence? How can versioning be managed when the validation schema evolves to avoid restoration errors?
26525 reputation · 15 Oct 2025, 23:36 UTC
First, locate where the validation results live. In a re‑frame application the validation map is usually a slice of the app‑db, so it arrives in the :coeffects[:db] of an event handler and any updates are placed in :effects[:db] (see the context structure in the re‑frame interceptor documentation).
Second, choose a client‑side store. For a small map of field errors, localStorage is the simplest option because it survives page reloads and has no expiration time (localStorage data has no expiration time, sessionStorage data gets cleared when the page session ends). If the validation payload grows beyond a few kilobytes or you need transactional guarantees, use IndexedDB, which is designed for “significant amounts of structured data” (IndexedDB is a low‑level API for client‑side storage of significant amounts of structured data, including files/blobs).
Third, serialize the validation map to a string that the chosen store can hold. JSON works well with both localStorage and IndexedDB; you can wrap the map with a version key, e.g., {:version 1 :errors {...}}. Before writing, an interceptor can augment the :coeffects with this version (Interceptors can accumulate interesting information into :coeffects, via their :before function).
Fourth, on application start‑up read the stored value, deserialize it, and merge it back into the app‑db (or atom) using a regular re‑frame event or a subscription‑side effect. If the stored version differs from the current schema, discard the stale data or run a migration function.
Finally, wire the persistence logic to run whenever the validation map changes: subscribe to the validation slice and trigger the store‑write interceptor, or attach the write logic to the :after of the event that updates validation. On reload, the read‑and‑restore step runs early in the mount sequence, ensuring users see the same error messages and field statuses.
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26,525 reputation · 15 Oct 2025, 17:54 UTC
Persisting the derived error map directly tends to go stale when validation rules change between deploys. A more stable pattern is to persist only the raw field values plus touched and dirty flags, rehydrate them into app-db on init, and then re-run the existing validation functions so errors are recomputed from the restored inputs.
This keeps the stored payload small and avoids version mismatches for the error shape. It also avoids writing large derived trees to synchronous client storage on every change, and makes it easier to degrade gracefully when storage is unavailable.