from movie_filter import MovieFilter
from relationship_filter import RelationshipFilter
from rdf_filter import RdfFilter
from cleaner import PipelineApplier

from Scripts.DataCleaning.data_output_models.bpe_corpus import BPE_corpus
from Scripts.DataCleaning.data_output_models.rdf_text_tasks import RDF_text_task_dataset
from Scripts.DataCleaning.data_output_models.rdf_completation_task import RDF_completation_task_dataset
from Scripts.DataCleaning.data_output_models.debug_csv import Debug_csv

import pandas as pd

RELATIONSHIP_FILTER_LIST = [
            "dbp-dbp:wikiPageUsesTemplate","w3:2000/01/rdf-schema#label","dbp-dbo:abstract",
            "dbp-dbo:wikiPageID","dbp-dbo:wikiPageRevisionID", "dbp-dbo:wikiPageDisambiguates",
            "w3:2002/07/owl#sameAs","dbp-dbp:image","dbp-dbo:wikiPageLength", "w3:2000/01/rdf-schema#comment",
            "dbp-dbo:thumbnail", "foaf:depiction", "w3:1999/02/22-rdf-syntax-ns#type", 
            "dbp-dbp:id","dbp-dbp:totalWidth", "w3:ns/prov#wasDerivedFrom", "dbp-dbp:n", "dbp-dbp:alt",
            "dbp-dbo:soundRecording", "dbp-dbp:align", "dbp-dbp:format", "dbp-dbp:n", 
            "dbp-dbp:filename", "dbp-dbp:wikt", "foaf:isPrimaryTopicOf", "dbp-dbp:quote", "foaf:homepage",
            "dbp-dbp:wordnet_type", "dbp-dbp:length"
            ]


class Pipeline():

    def __init__(self) -> None:
        self._movie_filter = MovieFilter()
        self._relationship_filter = RelationshipFilter()
        self._rdf_filter = RdfFilter()
        self._pipeline = PipelineApplier()

        self.task_bpe_corpus = BPE_corpus("./Assets/Dataset/Tmp/corpus.txt")
        self.task_rdf_text = RDF_text_task_dataset("./Assets/Dataset/Tmp/rdf_text.csv")
        self.task_rdf_completation = RDF_completation_task_dataset("./Assets/Dataset/Tmp/rdf_completation.csv")

        self._movie_filter.frequency_filter(50,3000)
        self._relationship_filter.frequency_filter(50, 2395627) # from 2718 to 3069 
        self._relationship_filter.delete_relationship_uri_by_list(RELATIONSHIP_FILTER_LIST)

    def other_filter(self):
        self._movie_filter.relation_filter("purl:dc/terms/subject",5,100)
        self._movie_filter.relation_filter("dbp-dbo:director",1,100)

    def _get_cleaned_movie_rows(self):
        movie_ids = self._movie_filter.get_movie_id()
        rel_ids = self._relationship_filter.get_relationship_id()

        for RDF in self._rdf_filter.yield_movie_abbreviated_rdfs(movie_ids,rel_ids):
            RDF = self._pipeline.drop_na_from_dataset(RDF)
            RDF = self._pipeline.regex_on_objects(RDF)
            RDF = self._pipeline.rdf_add_special_token(RDF)

            if RDF.empty:
                continue
            yield RDF


    def execute_task_bpe_corpus(self):
        for RDF in self._get_cleaned_movie_rows():
            RDF = self._pipeline.rebuild_by_movie(RDF)
            RDF = RDF[["Triple","Abstract"]]
            self.task_bpe_corpus.write_from_df(RDF)
        self._end_file_handler()


    def execute_tasks_rdf_text(self):
        for RDF in self._get_cleaned_movie_rows():
            RDF = self._pipeline.rebuild_by_movie(RDF)
            self.task_rdf_text.write(RDF)
        self._end_file_handler()


    def execute_task_rdf_completation(self):
        for RDF in self._get_cleaned_movie_rows():
            RDF["Triple"] = self._pipeline.build_triple(RDF)
            self.task_rdf_completation.write(RDF[["MovieID","Triple"]])
        self._end_file_handler()
        

    def _end_file_handler(self):
        self.task_bpe_corpus.close()
        self.task_rdf_text.close()
        self.task_rdf_completation.close()


    def execute_all_task(self):
        for RDF in self._get_cleaned_movie_rows():
            completation_RDF = RDF.copy()
            completation_RDF["Triple"] = self._pipeline.build_triple(completation_RDF)
            self.task_rdf_completation.write(completation_RDF[["MovieID","Triple"]])

            RDF = self._pipeline.rebuild_by_movie(RDF)

            self.task_rdf_text.write(RDF)
            self.task_bpe_corpus.write_from_df(RDF[["Triple","Abstract"]])

        self._end_file_handler()

    
    def use_toy_dataset(self):
        # CHOOSEN MOVIE:
        # The Dark Knight   : 117248
        # Inception         : 147074
        # The Avengers      : 113621
        # Cast Away         : 1123
        # The Departed      : 117586
        # American Psycho   : 90177
        # Avatar            : 71587
        # Django Unchained  : 138952
        # Spirited Away     : 144137
        # Knives Out        : 148025
        movie_list = [117248, 147074, 113621, 1123, 117586, 90177, 71587, 138952, 144137, 148025]
        self._movie_filter.MOVIE_FILTER = pd.DataFrame({"MovieID": movie_list})

    def generate_csv_debug_file(self, debug_path:str):
        debug_csv = Debug_csv(debug_path)

        for RDF in self._get_cleaned_movie_rows():
            debug_csv.write(RDF)

        debug_csv.close()


pipe = Pipeline()
pipe.use_toy_dataset()
pipe.other_filter()
# pipe.execute_all_task()
pipe.generate_csv_debug_file("Assets/Dataset/Tmp/debug.csv")