"""
file: rdf2pandas.py
auth: Peb Ruswono Aryan
desc: import data in RDF Data Cube (assumed in particular shape) from Graph to Pandas DataFrame
"""
from rdflib import Graph, Namespace, RDF, RDFS
import pandas as pd

QB = Namespace('http://purl.org/linked-data/cube#')
DCT = Namespace('http://purl.org/dc/terms/')

def short_name(uristr: str) -> str:
    hpos = uristr.rindex('#') if '#' in uristr else -1
    spos = uristr.rindex('/') if '/' in uristr else -1
    return uristr[max(hpos,spos)+1:]

def from_graph(g : Graph) -> pd.DataFrame :
    """
    import DataFrame from rdflib.Graph
    expects shape :
        ?ds RDF.type QB.DataSet
        ?ds QB.structure ?dsd
        ?dsd QB.component [QB.dimension ?dim] || ?dsd QB.component [QB.measure ?mea]
        ?obs QB.dataSet ?ds
        ?obs ?dim ?dimval || ?obs ?mea ?meaval
    """
    data = []
    columns = []
    dss = list(g.subjects(RDF.type, QB.DataSet))
    if len(dss)>0:
        ds = dss[0]
        dsds = list(g.objects(ds, QB.structure))
        if len(dsds)>0:
            dsd = dsds[0]

            dims = []
            meas = []
            for c in g.objects(dsd, QB.component):
                dim = g.value(c, QB.dimension)
                mea = g.value(c, QB.measure)
                if dim is not None:
                    dims.append(dim)
                elif mea is not None:
                    meas.append(mea)
            comps = dims + meas
            for c in comps:
                # try if there's some label annotation in the graph
                lbl = g.value(c, RDFS.label)
                if lbl is not None:
                    columns.append(lbl)
                    continue
                lbl = g.value(c, DCT.title)
                if lbl is not None:
                    columns.append(lbl)
                    continue
                lbl = short_name(str(c))
                columns.append(lbl)
        
        for obs in g.subjects(QB.dataSet, ds):
            row = []
            for c in comps:
                row.append(g.value(obs, c))
            data.append(row)
        
    df = pd.DataFrame(data, columns = columns)
    return df