import uuid # For UUID creation
from initDb import initDb # For database initialization
from wisski.api import Api, Pathbuilder, Entity # For WissKI API
import os # For environment variable loading
from dotenv import load_dotenv # For environment variable loading
import pandas as pd # For dataframe handling

def importLiterature(api, engine):
    print('Importing literature...')
    tableName = 'c__lit'
    bundleId = 'bafe9c3d3b640d4d1a16b104f367ac91'

    try:
        processedRows = pd.read_csv(f'./logs/{tableName}.csv')
    except FileNotFoundError:
        processedRows = pd.DataFrame(columns=['id', 'docId', 'uuid', 'uri'])

    # Load sources table
    literaturesTable = pd.read_sql_table(tableName, con=engine)


    # Create literatures
    for index, row in literaturesTable.iterrows():
        # For every row in table...
        if index < len(processedRows) and literaturesTable.loc[index, 'id'] == processedRows.loc[index, 'id']:
            # skip if already processed
            print(f'Skipping already processed literature {literaturesTable.loc[index, "id"]}')
            continue
        # Create Entity property dicts
        literatureValues = {}
        digitisationProcessValues = {'f32274ec0032b8778ba69d20108590cc': [str(uuid.uuid4())]}
        for key, value in row.items():
            # For every column in row...
            if (value is None) or (value == ''):
                #  skip if cell has no value
                continue
            # Properties of an entity have to be an array, so...
            value = str(value).replace('&###{{new_line}}###'.format(), '&')
            value = str(value).replace('###{{new_line}}###', '&')
            value = str(value).replace(' & ', '&')
            if '&' in str(value):
                # ...Explode "&"-separated values to array items
                value = [x.strip() for x in str(value).split('&')]
            else:
                # ...Or parse to array
                value = [value]
            # Map columns to fields. We use assignments for reification.
            match key:
                case 'id':
                    continue
                case 'f__uuid':
                    literatureValues['fd58e0884f7cf63f8436c2789fcd2745'] = value # UUID
                case 'f__9990_kommentar':
                    literatureValues['f3208633f7767cc9f5e44e768818df20'] = value # Comment
                case 'f__8270_verfasser':
                    literatureValues['f60a88060c75068b4bf2eefd5221793f'] = value # Creator
                case 'f__8324_ersch_jahr':
                    literatureValues['fdae7bd743ae58bf623feca3a26bcf6c'] = value # Date
                case 'f__8280_hrsg':
                    literatureValues['fd0bc706876adee304892f8f9e34567f'] = value # Editor
                case 'f__8346_signatur':
                    literatureValues['fb434c214be21f7e82a851d6524c2850'] = value # Identifier
                case 'f__9970_schlagwort':
                    literatureValues['f1a55055944adf5d4e866a1768633a7f'] = value # Keyword
                case 'f__8200_lit_dok_nr_':
                    literatureValues['f3bdd54b9ea5808a571200e9c60e103e'] = value # Literature Document Identifier
                case 'f__9971_sw_goldschmied':
                    literatureValues['f21a286fec5d48ea238c10877ee2b0db'] = value # Mentioned Actor
                case 'f__8308_bibl_zusatz':
                    literatureValues['f1674a743a13a3d74b0c6ebb2cf0043f'] = value # Note
                case 'f__8319_seitenangabe':
                    literatureValues['f0d1716a40498f52abd4a6522aa5f3ef'] = value #  Pages
                case 'f__8320_ersch_ort':
                    literatureValues['fc3cafc0f542cef2a0e1189873ff58a3'] = value #  Publication Place
                case 'f__8300_serientitel':
                    literatureValues['f660f34eb7091c1b0f4b492e49a0e71b'] = value #  Series Title
                case 'f__8330_lit_kurzt_':
                    literatureValues['f84416d4380cdd30e8b9fcea57f58957'] = value # Shorttitle
                case 'f__8307_titelzusatz':
                    literatureValues['f8521679ac8f6441ddb086f1c5ed7528'] = value # Subtitle
                case 'f__8290_titel':
                    literatureValues['fa1ae40cc9940569d5a1e3ea13e33488'] = value # Title
                case 'f__8260_art':
                    literatureValues['f92c6453d265a952a56252e7d93cedea'] = value # Type
                # Digitisation Process
                case 'f__9900_datum_erfassung':
                    digitisationProcessValues['f1f5dd22371e5c1de41e0fb099e0e862'] = value  # Recording date
                case 'f__99ae_datum_aenderung':
                    digitisationProcessValues['f8976c6a9e5d91fe9caba8a57c27f204'] = value  # Change date
                case 'f__efbm_bem_erfassung':
                    digitisationProcessValues['f78a6310d13c717b82ddba814ac59024'] = value # Recording note
                case _:
                    print(f'{key} is not a valid field, skipping.')

        # Create Digitisation Process
        digitisationProcess = Entity(api=api, fields=digitisationProcessValues, bundle_id='b22e6c47ccb3ab8a974b37279e1bc33b')
        api.save(digitisationProcess)

        # Set Digitisation Process
        literatureValues['f59a2ad5cce3e51f172215ea88afac41'] = [digitisationProcessValues['f32274ec0032b8778ba69d20108590cc'][0]] # Digitisation Process

        # Create Material
        literature = Entity(api=api, fields=literatureValues, bundle_id='bafe9c3d3b640d4d1a16b104f367ac91')
        api.save(literature)

        print(f'Created literature {index}: {literature.uri} of {len(literaturesTable)}')

        # Write log
        processedRows = processedRows._append({'id': row['id'], 'docId': literatureValues['f3bdd54b9ea5808a571200e9c60e103e'][0], 'uuid': literatureValues['fd58e0884f7cf63f8436c2789fcd2745'][0], 'uri': literature.uri}, ignore_index=True)
        processedRows.to_csv(f'./logs/{tableName}.csv', index=False)

    print('finish')