import os
import datasets
from datasets import DatasetBuilder, SplitGenerator, DownloadConfig, load_dataset, DownloadManager, DatasetInfo, GeneratorBasedBuilder
from rdflib import Graph, URIRef, Literal, BNode
from rdflib.namespace import RDF, RDFS, OWL, XSD, Namespace, NamespaceManager
from datasets.features import Features, Value

SCHEMA = Namespace('http://schema.org/')

YAGO = Namespace('http://yago-knowledge.org/resource/')

class YAGO45DatasetBuilder(GeneratorBasedBuilder):
    VERSION = "1.0.1"

    def _info(self):
        return DatasetInfo(
            description="A subset of the YAGO 4.5 dataset maintaining only English labels",
            citation="@article{suchanek2023integrating,title={Integrating the Wikidata Taxonomy into YAGO},author={Suchanek, Fabian M and Alam, Mehwish and Bonald, Thomas and Paris, Pierre-Henri and Soria, Jules},journal={arXiv preprint arXiv:2308.11884},year={2023}}",
            homepage="https://yago-knowledge.org/",
            license="https://creativecommons.org/licenses/by-sa/3.0/",
            features=Features({
                'subject': Value('string'),
                'predicate': Value('string'),
                'object': Value('string')
            })
        )
    
    def _split_generators(self, dl_manager):
        # Download and extract the dataset
        # Define splits for each chunk of your dataset.
        
        # Download and extract the dataset files
        facts, taxonomy = dl_manager.download_and_extract(["facts.tar.gz", "yago-taxonomy.ttl"])

        facts = os.path.join(facts, "facts/")

        # Define splits for each chunk of your dataset.
        chunk_paths = [os.path.join(facts, chunk) for chunk in os.listdir(facts) if chunk.endswith('.nt')] + [taxonomy]
        return [SplitGenerator(name=datasets.Split.TRAIN, 
                               gen_kwargs={'chunk_paths': chunk_paths})]
    
    def _generate_examples(self, chunk_paths):
        # Load the chunks into an rdflib graph
        # Yield individual triples from the graph
        id_ = 0
        for chunk_path in chunk_paths:
            graph = Graph(bind_namespaces="core")
            graph.parse(chunk_path)
            
            # Yield individual triples from the graph as N3
            for (s, p, o) in graph.triples((None, None, None)):
                yield id_, {
                    'subject': s.n3(),
                    'predicate': p.n3(),
                    'object': o.n3()
                }
                id_ += 1

from rdflib.util import from_n3

def triples(features):
    try:
        subject_node = from_n3(features['subject'])
        predicate_node = from_n3(features['predicate'])
        object_node = from_n3(features['object'])
        return (subject_node, predicate_node, object_node)
    except Exception as e:
        print(f"Error transforming features {features}: {e}")
        return (None, None, None)