Python API#

CLI#

OME_IRIS.cli.build_parser() → ArgumentParser[source]#

OME_IRIS.cli.main() → int[source]#

Fetch#

class OME_IRIS.fetch.FetchResult(downloaded: 'int', skipped: 'int', missing_urls: 'list[str]', failed: 'list[str]' = <factory>, downloaded_items: 'list[str]' = <factory>, skipped_items: 'list[str]' = <factory>)[source]#

downloaded: int#

downloaded_items: list[str]#

failed: list[str]#

missing_urls: list[str]#

skipped: int#

skipped_items: list[str]#

OME_IRIS.fetch.fetch_datasets(manifests_dir: Path, data_dir: Path, dataset_id: str | None = None, tier: str | None = None, verbose: bool = False, silent: bool = False) → FetchResult[source]#

OME_IRIS.fetch.main() → int[source]#

Dataset subsets#

class OME_IRIS.datasets.DownloadResult(downloaded: 'int' = 0, skipped: 'int' = 0, validated: 'int' = 0, failed: 'list[str]' = <factory>, downloaded_items: 'list[str]' = <factory>, skipped_items: 'list[str]' = <factory>, validated_items: 'list[str]' = <factory>, manifest_path: 'Path | None' = None)[source]#

downloaded: int = 0#

downloaded_items: list[str]#

failed: list[str]#

manifest_path: Path | None = None#

skipped: int = 0#

skipped_items: list[str]#

validated: int = 0#

validated_items: list[str]#

OME_IRIS.datasets.download(dataset: str, output_dir: str | Path, subset: dict[str, Any] | None = None, *, preset: str | None = None, manifests_dir: str | Path | None = None, validate_only: bool = False, silent: bool = False) → DownloadResult[source]#: Download or validate a reproducible subset of a known dataset.

Verify#

class OME_IRIS.verify.VerifyResult(ok: 'bool', issues: 'list[str]')[source]#

issues: list[str]#

ok: bool#

OME_IRIS.verify.main() → int[source]#

OME_IRIS.verify.verify_datasets(manifests_dir: Path, data_dir: Path) → VerifyResult[source]#

Scaffold#

class OME_IRIS.scaffold.ScaffoldResult(dataset_id: 'str', manifest_path: 'Path', csv_row: 'str')[source]#

csv_row: str#

dataset_id: str#

manifest_path: Path#

OME_IRIS.scaffold.scaffold_dataset_manifest(source_path: str, manifests_dir: Path, dataset_id: str | None = None, dataset_name: str | None = None, tier: str = 'small', license_name: str = 'TBD', source_repository: str = '', source_url: str = '', include_directory_entry: bool = False, directory_path: str = 'images', archive_format: str = 'zip', append_csv: bool = False, catalog_csv: Path | None = None, force: bool = False) → ScaffoldResult[source]#