import type { MetaStatistics } from './meta-statistics';
import type { RParseRequestFromFile, RParseRequestFromText } from '../r-bridge/retriever';
import type { PipelineOutput } from '../core/steps/pipeline/pipeline';
import { DEFAULT_DATAFLOW_PIPELINE } from '../core/steps/pipeline/default-pipelines';
import type { RShell } from '../r-bridge/shell';
import type { FeatureSelection, FeatureStatistics } from './features/feature';
import type { FlowrConfigOptions } from '../config';
/**
 * By default, {@link extractUsageStatistics} requires a generator, but sometimes you already know all the files
 * that you want to process. This function simply reps your requests as a generator.
 */
export declare function staticRequests(...requests: (RParseRequestFromText | RParseRequestFromFile)[]): AsyncGenerator<RParseRequestFromText | RParseRequestFromFile>;
type DataflowResult = PipelineOutput<typeof DEFAULT_DATAFLOW_PIPELINE>;
/**
 * Extract all wanted statistic information from a set of requests using the presented R session.
 *
 * @param shell     - The R session to use
 * @param config    - The flowr config
 * @param onRequest - A callback that is called at the beginning of each request, this may be used to debug the requests.
 * @param features  - The features to extract (see {@link allFeatureNames}).
 * @param requests  - The requests to extract the features from. May generate them on demand (e.g., by traversing a folder).
 * 										If your request is statically known, you can use {@link staticRequests} to create this generator.
 * @param rootPath  - The root path to the project, this is used to relativize the file paths in the statistics.
 */
export declare function extractUsageStatistics<T extends RParseRequestFromText | RParseRequestFromFile>(shell: RShell, config: FlowrConfigOptions, onRequest: (request: T) => void, features: FeatureSelection, requests: AsyncGenerator<T>, rootPath?: string): Promise<{
    features: FeatureStatistics;
    meta: MetaStatistics;
    outputs: Map<T, DataflowResult>;
}>;
export {};