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"""
Part of the BlackStar filesystem (bsfs) module.
A copy of the license is provided with the project.
Author: Matthias Baumgartner, 2022
"""
# imports
from collections import defaultdict
import typing
# bsfs imports
from bsfs.utils import URI
# exports
__all__: typing.Sequence[str] = (
'to_list_view',
'to_dict_view',
)
## code ##
def to_list_view(
triples,
# aggregators
node: bool,
path: bool,
value: bool, # pylint: disable=unused-argument
):
"""Return an iterator over results.
Dependent on the *node*, *path*, and *value* flags,
the respective component is omitted.
"""
if node and path:
return iter(val for _, _, val in triples)
if node:
return iter((pred, val) for _, pred, val in triples)
if path:
return iter((subj, val) for subj, _, val in triples)
return iter((subj, pred, val) for subj, pred, val in triples)
def to_dict_view(
triples,
# context
one_node: bool,
one_path: bool,
unique_paths: typing.Set[typing.Union[URI, typing.Iterable[URI]]],
# aggregators
node: bool,
path: bool,
value: bool,
) -> typing.Any:
"""Return a dict of results.
Note that triples are materialized to create this view.
The returned structure depends on the *node*, *path*, and *value* flags.
If all flags are set to False, returns a dict(node -> dict(path -> set(values))).
Setting a flag to true omits or simplifies the respective component (if possible).
"""
# NOTE: To create a dict, we need to materialize or make further assumptions
# (e.g., sorted in a specific order).
data: typing.Any # disable type checks on data since it's very flexibly typed.
# FIXME: type of data can be overwritten later on (if value)
if node and path:
data = set()
elif node ^ path:
data = defaultdict(set)
else:
data = defaultdict(lambda: defaultdict(set))
for subj, pred, val in triples:
unique = pred in unique_paths
if node and path:
if value and unique and one_node and one_path:
return val
data.add(val)
elif node:
# remove node from result, group by predicate
if value and unique and one_node:
data[pred] = val
else:
data[pred].add(val)
elif path:
# remove predicate from result, group by node
if value and unique and one_path:
data[subj] = val
else:
data[subj].add(val)
else:
if value and unique:
data[subj][pred] = val
else:
data[subj][pred].add(val)
# FIXME: Combine multiple Nodes instances into one?
# convert defaultdict to ordinary dict
if node and path:
return data
if node ^ path:
return dict(data)
return {key: dict(val) for key, val in data.items()}
## EOF ##
|
