photochk/Sources/Photochk/Core/Concurrency.swift

import Foundation

/// 同時実行数を抑えつつ並列に変換し、入力と同じ順序で結果を返す。
///
/// 画像デコードや Vision の推論は CPU を使い切るので、無制限に投げるより
/// コア数程度に抑えたほうが速く、メモリも安定する。
func mapConcurrently<Item: Sendable, Output: Sendable>(
    _ items: [Item],
    limit: Int = max(2, ProcessInfo.processInfo.activeProcessorCount),
    onProgress: (@Sendable (Int) -> Void)? = nil,
    _ transform: @escaping @Sendable (Item) async -> Output
) async throws -> [Output] {
    guard !items.isEmpty else { return [] }

    var results = [Output?](repeating: nil, count: items.count)

    try await withThrowingTaskGroup(of: (Int, Output).self) { group in
        var next = 0
        let initial = min(limit, items.count)
        while next < initial {
            let index = next
            group.addTask { (index, await transform(items[index])) }
            next += 1
        }

        var finished = 0
        while let (index, value) = try await group.next() {
            results[index] = value
            finished += 1
            onProgress?(finished)
            try Task.checkCancellation()

            if next < items.count {
                let index = next
                group.addTask { (index, await transform(items[index])) }
                next += 1
            }
        }
    }

    return results.compactMap { $0 }
}