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)