「data-loading」の検索結果

Discover connected data sources, add new data connectors through a user-confirmed form, inspect table metadata, and run bounded read-only probes when the current workspace data is insufficient.

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DALI imperative dynamic mode (`nvidia.dali.experimental.dynamic`, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks.

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Symfony UX LiveComponent for reactive server-rendered UI -- components that re-render via AJAX on user interaction, zero JavaScript required. Use when building live search, real-time filtering, dynamic forms, inline validation, dependent selects, auto-save, polling, deferred/lazy rendering, or any UI that updates itself based on user input. Code triggers: AsLiveComponent, LiveProp, LiveAction, data-model, data-loading, data-live-action-url, ComponentWithFormTrait, LiveListener, emit, defer, lazy, polling. Also trigger when the user asks "how to build a search that filters as I type", "how to validate a form in real-time", "how to make a reactive component in PHP", "how to build dependent selects", "how to defer component rendering", "how to communicate between components via emit", "how to bind a form to a LiveComponent". Do NOT trigger for static reusable UI without reactivity (use twig-component), pure client-side JS behavior (use stimulus), or page-level navigation (use turbo).

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TanStack Router best practices for type-safe routing, file-based routing, data loading, search params, and navigation in React. Use when building React SPAs with complex routing, implementing type-safe search params, setting up route loaders, integrating with TanStack Query, or configuring code splitting and preloading.

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Route loader option, loaderDeps for cache keys, staleTime/gcTime/ defaultPreloadStaleTime SWR caching, pendingComponent/pendingMs/ pendingMinMs, errorComponent/onError/onCatch, beforeLoad, router context and createRootRouteWithContext DI pattern, router.invalidate, Await component, deferred data loading with unawaited promises.

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Patterns for loading PDE simulation datasets (PDEBench, PhiFlow, JAX-CFD) from HDF5 files. Handles layout detection (single tensor vs separate variables), spatial/temporal downsampling, multi-variable systems, HuggingFace and DaRUS data sources, and efficient PyTorch DataLoader creation. Use when preparing PDE data for neural operator training.

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Detects route data fetched in useEffect instead of loaders, server/client API leaks across loader boundaries, and missing HydrateFallback in React Router v7 framework mode.

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