Python: module datazen.parsing

datazen.parsing

index
/home/vkottler/src/vkottler/workspace/datazen/datazen/parsing.py

datazen - APIs for loading raw data from files.

Modules

Functions

dedup_dict_lists(data: Dict[Any, Any]) -> Dict[Any, Any]: Finds list elements in a dictionary and removes duplicate entries, mutates
the original list.

load(path: Union[pathlib.Path, str, NoneType], variables: Dict[str, Any], dict_to_update: Dict[str, Any], expect_overwrite: bool = False, is_template: bool = True, logger: logging.Logger = <Logger datazen.parsing (WARNING)>, **kwargs) -> vcorelib.io.types.LoadResult: Load raw file data and meld it into an existing dictionary. Update
the result as if it's a template using the provided variables.

set_file_hash(hashes: Dict[str, Any], path: Union[pathlib.Path, str, NoneType], set_new: bool = True) -> bool: Evaluate a hash dictionary and update it on a miss.

template_preprocessor_factory(variables: Dict[str, Any], is_template: bool, stack: contextlib.ExitStack) -> Callable[[Union[TextIO, _io.StringIO]], Union[TextIO, _io.StringIO]]: Create a stream-processing function for data decoding.

Data
		ARBITER = <vcorelib.io.arbiter.DataArbiter object> DataStream = typing.Union[typing.TextIO, _io.StringIO] GenericDict = typing.Dict[typing.Any, typing.Any] GenericStrDict = typing.Dict[str, typing.Any] LOG = <Logger datazen.parsing (WARNING)> Pathlike = typing.Union[pathlib.Path, str, NoneType] StreamProcessor = typing.Callable[[typing.Union[typing.TextIO, _io...gIO]], typing.Union[typing.TextIO, _io.StringIO]]