def _from_dataframe(row: Series, na: Union[Any, List[Any]], nesting: str) -> Resource: new_na = row.replace(na, np.nan) no_na = new_na.dropna() items = list(no_na.items()) data = deflatten(items, nesting) return from_json(data, None)
def _map_one(self, data: Union[Path, Dict], mappings: List[Mapping], nas: List[Any]) -> List[Resource]: variables = { "forge": self.forge, "x": self._load_one(data), } mapped = (_apply_rules(x.rules, variables) for x in mappings) return [from_json(x, nas) for x in mapped]
def _to_resource(record: Dict) -> Resource: # TODO This operation might be abstracted in core when other stores will be implemented. resource = from_json(record["data"], None) resource._store_metadata = wrap_dict(record["metadata"]) resource._synchronized = True return resource
def from_json(self, data: Union[Dict, List[Dict]], na: Union[Any, List[Any]] = None ) -> Union[Resource, List[Resource]]: return from_json(data, na)