Defines the reusable component API, state model, integration expectations, examples, and tests for data table. This reference fixes the adoption boundary, failure behavior, and observable evidence while leaving environment-specific limits configurable.
Package status: reference context ready for human review. The contract and test scenarios are complete, but no claim is made that an adopting implementation has passed them.
Decision
For Data table, adopt a reusable state and interaction contract using native semantics where available. Implement the behavior through one authoritative write path, typed interfaces, explicit state, and idempotent side-effect handling. This implementation block focuses specifically on component contract and tests. This package is a reference contract: the adopting team must choose numeric limits, providers, jurisdictions, and operational owners from evidence in its own environment.
Scope
- The Data table actors, inputs, outputs, states, policy or schema versions, and externally visible outcomes required for the component contract and tests focus of this implementation block.
- Primary and alternate interfaces, background work, caches, integrations, support paths, and evidence that can exercise the same boundary.
- Adoption-specific configuration, rollout, recovery, and verification responsibilities needed to apply the reference safely.
Outside this block
- Choosing a universal vendor, framework, jurisdiction, numeric threshold, retention period, or service-level objective for every adopter.
- Claiming that packaged scenarios have run against a downstream implementation or that this reference grants legal, security, or accessibility certification.
Contract
- Define trigger, open or active, loading, success, empty, invalid, error, disabled, and dismissal states that the pattern can enter.
- Specify keyboard input, focus entry and return, accessible name, announcements, pointer behavior, and touch target behavior together.
- Make destructive, irreversible, or external effects explicit and prevent duplicate activation while work is pending.
- Keep content hierarchy and actions usable at narrow widths, high zoom, text expansion, forced colors, and reduced motion.
- Validate inputs once at the boundary and preserve the normalized representation used by downstream logic.
- Persist the business transition before or atomically with an outbox record; consumers deduplicate by durable operation identity.
- Expose table name, row and column headers, sort, filter, selection, edit, totals, position, and state programmatically while preserving a coherent source, reading, and keyboard order.
- Keep identity and focus stable through pagination, virtualization, responsive transformation, async refresh, inline errors, and bulk actions and provide accessible empty and loading states.
- For the component contract and tests variant, enforce this declared boundary: defines the reusable component api, state model, integration expectations, examples, and tests for data table.
Implementation guidance
- Ship additive storage and interface changes first, backfill observably, then retire old paths after compatibility evidence.
- Model Data table inputs, outputs, actors, states, invariants, side effects, and evidence before selecting framework or vendor details.
- Store the applicable Data table contract or policy version with material state so migrations, replay, and support decisions remain attributable.
- Introduce the path behind controlled rollout, compare expected and observed outcomes, and keep a tested recovery route until adoption evidence is complete.
Failure handling and safeguards
- On failed action, preserve relevant input and focus, announce the result, and return the component to a state with a safe recovery path.
- Invalid or contradictory Data table state is rejected or quarantined; the implementation never guesses a value that broadens authority or duplicates an effect.
- Retries are bounded and use durable identity; after exhaustion, work reaches an inspectable terminal state with an accountable owner.
Verification and operations
- Inject dependency failure before and after persistence and prove that retry converges on one externally visible outcome.
- Monitor Data table success, denial, validation failure, dependency failure, retry exhaustion, and recovery by contract version without sensitive payload dimensions.
- Re-run paired positive and negative fixtures after policy, schema, dependency, migration, or boundary changes and preserve the resulting evidence.
Adoption assumptions
- Names and values in the example are a concrete fixture, not universal defaults; adopters replace them through documented evidence and ownership.
- The adopting system can provide authenticated identity, durable operation or record versions, bounded telemetry, and a controlled path for change.
The executable-looking examples in this package are fixtures and acceptance contracts. Run the collection validator to check structure and metadata, then translate and execute the scenarios in the target repository before recording implementation evidence.