import type { GroupedRow, TimeGrain } from '../db/repositories/usage-repository.js';
/**
 * Filling in the buckets that had no activity.
 *
 * `daily --days 30` returned only the days that HAD data -- ten rows for a
 * thirty-day window, with nothing to say the other twenty existed. Reading a
 * trend off that is not merely harder, it is actively misleading: the gaps are
 * invisible, so an ordinary day renders immediately beside one three weeks
 * earlier and looks like a spike next to it.
 *
 * A zero row is not a fabricated number. It asserts that no usage was recorded
 * in that bucket, which is exactly what the absence of rows meant -- it just
 * says it where a reader can see it. Every filled row carries `zeroFilled: true`
 * so a consumer can tell an observed zero from a constructed one.
 */
/** A bucket that was constructed rather than observed. */
export interface TimeBucket extends GroupedRow {
    zeroFilled?: boolean;
}
/**
 * Zero-filling an hourly range over all time would generate tens of thousands
 * of rows nobody asked for, so it is bounded and the caller is told when the
 * bound bit, rather than quietly returning a partial series.
 */
export declare const MAX_ZERO_FILLED_BUCKETS = 5000;
export interface ZeroFillResult {
    rows: TimeBucket[];
    /** Set when the range was too large to fill, explaining why it was not. */
    note?: string;
}
/**
 * Returns the observed rows with every empty bucket in range filled in.
 *
 * @param bounds The window to fill. When the caller gave no explicit period,
 *   pass the first and last activity instead -- filling from the epoch would
 *   invent thousands of rows describing time before the data existed.
 */
export declare function zeroFill(rows: GroupedRow[], grain: TimeGrain, bounds: {
    since?: string;
    until?: string;
}): ZeroFillResult;