For very big datasets, we might not need to load every features, it would be usefull to load only usefull features
class Sample:
def load(self, feature_identifiers: list[FeatureIdentifier]).
...
As we are using the pycgns lib, we might be forced to load the whole mesh for each Sample, but we can discard useless features from the loaded tree before processing the next Sample.