Function run

explainshell/extraction/runner.py:640–687

Unified dispatcher for all execution modes. - ``batch_size`` set → batch mode (requires ``BatchExtractor``). - ``jobs > 1`` → parallel mode via thread pool. - otherwise → sequential.

(
    extractor: Extractor,
    gz_files: list[str],
    *,
    manifest: BatchManifestWriter | None = None,
    batch_size: int | None = None,
    jobs: int = 1,
    on_start: Callable[[str], None] | None = None,
    on_result: Callable[[str, ExtractionResult], None] | None = None,
)

def run(
    extractor: Extractor,
    gz_files: list[str],
    *,
    manifest: BatchManifestWriter | None = None,
    batch_size: int | None = None,
    jobs: int = 1,
    on_start: Callable[[str], None] | None = None,
    on_result: Callable[[str, ExtractionResult], None] | None = None,
) -> BatchResult:
    """Unified dispatcher for all execution modes.

    - ``batch_size`` set → batch mode (requires ``BatchExtractor``).
    - ``jobs > 1`` → parallel mode via thread pool.
    - otherwise → sequential.
    """
    if batch_size is not None:
        if batch_size < 1:
            raise ValueError(f"batch_size must be >= 1 (got {batch_size})")
        if not isinstance(extractor, BatchExtractor):
            raise TypeError(
                f"batch mode requires a BatchExtractor (got {type(extractor).__name__})"
            )
        if manifest is None:
            manifest = _NullBatchManifestWriter()
        return run_batch(
            extractor,
            gz_files,
            batch_size=batch_size,
            jobs=jobs,
            on_start=on_start,
            on_result=on_result,
            manifest=manifest,
        )
    if jobs > 1:
        return run_parallel(
            extractor,
            gz_files,
            jobs,
            on_start=on_start,
            on_result=on_result,
        )
    return run_sequential(
        extractor,
        gz_files,
        on_start=on_start,
        on_result=on_result,
    )


def run_collected(