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fix(table-core): correct number-range, filter-depth, autoRemove, and custom faceting semantics#6503
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fix(table-core): correct number-range, filter-depth, autoRemove, and custom faceting semantics #6503
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -283,25 +283,33 @@ When filtering is performed on the server, the rows loaded into the browser may | ||
| Each factory receives the table and a column ID, then returns a function that resolves the faceted result. The regular column APIs will return the server-provided values. | ||
| Factories are resolved once per table and column, but the function each factory returns runs on every read; the table does not cache its result. Read live values inside that returned function (from a signal, store, or `table.options.meta`) so updated server facets show up immediately, and memoize inside the factory if the calculation is expensive. | ||
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| ```ts | ||
| const serverFacets = await fetch('/api/faceting').then((res) => res.json()) | ||
| // `local` is your Alpine.reactive state, refreshed when facets arrive | ||
| async function loadFacets() { | ||
| local.serverFacets = await fetch('/api/faceting').then((res) => res.json()) | ||
| } | ||
| const features = tableFeatures({ | ||
| columnFacetingFeature, | ||
| facetedUniqueValues: (_table, columnId) => () => { | ||
| const uniqueValueMap = new Map<string, number>() | ||
| // Populate the map from serverFacets data for columnId. | ||
| return uniqueValueMap | ||
| // The returned functions run on every read and table.options stays in | ||
| // sync with the latest render, so read live data through options.meta | ||
| facetedUniqueValues: (table, columnId) => () => { | ||
| const serverFacets = table.options.meta?.serverFacets | ||
| return new Map<string, number>(serverFacets?.uniqueValues[columnId] ?? []) | ||
| }, | ||
| facetedMinMaxValues: (_table, columnId) => () => { | ||
| // Read the range from serverFacets data for columnId. | ||
| return [min, max] | ||
| facetedMinMaxValues: (table, columnId) => () => { | ||
| return table.options.meta?.serverFacets?.minMaxValues[columnId] | ||
| }, | ||
| }) | ||
| const table = createTable({ | ||
| features, | ||
| columns, | ||
| get meta() { | ||
| return { serverFacets: local.serverFacets } | ||
| }, | ||
| get data() { | ||
| return local.data | ||
| }, | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -304,26 +304,29 @@ When filtering is performed on the server, the rows loaded into the browser may | ||
| Each factory receives the table and a column ID, then returns a function that resolves the faceted result. The regular column APIs will return the server-provided values. | ||
| ```ts | ||
| const serverFacets = await fetch('/api/faceting').then((res) => res.json()) | ||
| Factories are resolved once per table and column, but the function each factory returns runs on every read; the table does not cache its result. Read live values inside that returned function (from a signal, store, or `table.options.meta`) so updated server facets show up immediately, and memoize inside the factory if the calculation is expensive. | ||
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| ```ts | ||
| // `this.serverFacets` is a @tracked field on your component, set when | ||
| // the facet request resolves | ||
| const features = tableFeatures({ | ||
| columnFacetingFeature, | ||
| facetedUniqueValues: (_table, columnId) => () => { | ||
| const uniqueValueMap = new Map<string, number>() | ||
| // Populate the map from serverFacets data for columnId. | ||
| return uniqueValueMap | ||
| // The returned functions run on every read and table.options stays in | ||
| // sync with the latest render, so read live data through options.meta | ||
| facetedUniqueValues: (table, columnId) => () => { | ||
| const serverFacets = table.options.meta?.serverFacets | ||
| return new Map<string, number>(serverFacets?.uniqueValues[columnId] ?? []) | ||
| }, | ||
| facetedMinMaxValues: (_table, columnId) => () => { | ||
| // Read the range from serverFacets data for columnId. | ||
| return [min, max] | ||
| facetedMinMaxValues: (table, columnId) => () => { | ||
| return table.options.meta?.serverFacets?.minMaxValues[columnId] | ||
| }, | ||
| }) | ||
| // Inside your Glimmer component: | ||
| table = useTable(() => ({ | ||
| features, | ||
| columns, | ||
| meta: { serverFacets: this.serverFacets }, | ||
| data: this.data, | ||
| })) | ||
| ``` | ||
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📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win
🧩 Analysis chain
🏁 Script executed:
Repository: TanStack/table
Length of output: 234
🏁 Script executed:
Repository: TanStack/table
Length of output: 50370
Split or relabel the step-4 line.
Step 4 currently merges PR
#6443(#5801expansion reset) and also describes Cluster 5 filtering fixes (#6007,#5987,#6101,#6081). The filtering fixes do not have a consolidated PR listed, so maintainers may treat the wrong PR as the vehicle for Cluster 5. Split this into separate steps, or replace the parenthetical with the actual Cluster 5 PR when available.🤖 Prompt for AI Agents