98 lines
3.8 KiB
Python
98 lines
3.8 KiB
Python
import uuid # For UUID creation
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from initDb import initDb # For database initialization
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from wisski.api import Api, Pathbuilder, Entity # For WissKI API
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import os # For environment variable loading
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from dotenv import load_dotenv # For environment variable loading
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import pandas as pd # For dataframe handling
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# Initialize the database
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print('Initializing the database...')
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engine, metadata, Session = initDb(True, './schemas/')
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if engine == False:
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print('Database initialization failed.')
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exit()
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# Load the environment variables
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load_dotenv()
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# Initialize the WissKI API
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print('Initializing the WissKI API...')
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api_url = os.getenv('API_URL')
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auth = (os.getenv('API_USERNAME'), os.getenv('API_PASSWORD'))
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headers = {"Cache-Control": "no-cache"}
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api = Api(api_url, auth, headers)
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api.pathbuilder = api.get_pathbuilder('default')
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tableName = "c__3330_todes_dat_"
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bundleId = 'b487c08016f572b9ecf3f9173339fec3'
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try:
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processedRows = pd.read_csv(f'./logs/processed-{tableName}.csv')
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except FileNotFoundError:
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processedRows = pd.DataFrame(columns=['docId', 'uuid', 'uri'])
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# Load sources table
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sqlTable = pd.read_sql_table(tableName, con=engine)
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entityValues = {}
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# Create entities
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for index, row in sqlTable.iterrows():
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# For every row in table...
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if index < len(processedRows) and sqlTable.iloc[index, 'docId'] == processedRows.iloc[index, 'docId']:
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# skip if already processed
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print(f'Skipping already processed entity {sqlTable.iloc[index, 0]}')
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continue
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# Create Entity property dicts
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entityValues = {}
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for key, value in row.items():
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# For every column in row...
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if (value is None) or (value == ''):
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# skip if cell has no value
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continue
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# Properties of an entity have to be an array, so...
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if '&' in str(value):
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# ...Explode "&"-separated values to array items
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value = [x.strip() for x in str(value).split('&')]
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else:
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# ...Or parse to array
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value = [value]
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# Map columns to fields. We use assignments for reification.
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docId = ''
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match key:
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case 'id':
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docId = value[0]
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case 'f__uuid':
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entityValues['f8beb0d372a5cf6f1668c47acf7e53cd'] = value # UUID
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uuid = value[0]
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case 'f__3330_todes_dat_':
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entityValues['f385a8c323f0a2f49d8eb175e1535b1b'] = value # Death date
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case 'f__33ls_lit__stelle':
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entityValues['fb4f168aa6a73169ef0350408a6260cc'] = value # Literature Reference
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case 'f__33lt_lit__kurztitel':
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entityValues['fd4ed8828d72a575f8609ba2c442b4b2'] = value # Literature short title
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case 'f__33bm_bem_tod':
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entityValues['f3028661430081ae44aa950abe0afbac'] = value # Note
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case 'f__3350_tod_ort':
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entityValues['fd80c2c8ba4c64c01e9c46ac7ae00d93'] = value # Place
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case 'f__33qs_quelle_stelle':
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entityValues['fd98cf7fbc0de4529e2a2d5e0b0c28bf'] = value # Source reference
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case 'f__33qt_quelle_kurztitel':
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entityValues['f973818e6c3d36ddd44ba3a713e308e6'] = value # Source short title
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case 'f__710t_art_ereignis':
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entityValues['fc039c43502b3525a92a8330d91f7944'] = value # Event type
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case _:
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print(f'{key} is not a valid field, skipping.')
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# Create Material
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entity = Entity(api=api, fields=entityValues, bundle_id=bundleId)
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api.save(entity)
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print(f'Created entity {index}: {entity.uri} of {len(sqlTable)}')
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# Write log
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processedRows = processedRows._append({'docId': docId, 'uuid': fUuid, 'uri': entity.uri}, ignore_index=True)
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processedRows.to_csv(f'./logs/processed-{tableName}.csv', index=False)
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print('finish')
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