Code fragments of main.py

• import psycopg2
• import os
• import json
• conn = psycopg2.connect(database=os.environ["DB_NAME"], user=os.environ["DATA_SOURCE_USERNAME"], host=os.environ["DATA_SOURCE_HOST"], password=os.environ["DATA_SOURCE_PASSWORD"], port=os.environ["DATA_SOURCE_PORT"] )
• conn = psycopg2.connect(database=os.environ["DB_NAME"], user=os.environ["DATA_SOURCE_USERNAME"], host=os.environ["DATA_SOURCE_HOST"], password=os.environ["DATA_SOURCE_PASSWORD"], port=os.environ["DATA_SOURCE_PORT"] )
• cursor = conn.cursor()
• cursor.execute("SELECT * FROM supplier_ratings")
• ratings = cursor.fetchall()
• # entry: (1, 'Supplier 2448', 'GmbH', 'In time', 20, 6, 456)
• distinct_suppliers = list({r[1] for r in ratings})
• def cnt_in_time(supplier):
• return sum(1 for x in ratings if x[3] == "In time" and x[1] == supplier)
• def cnt_occ(supplier):
• return sum(1 for x in ratings if x[1] == supplier)
• def calc_score(cnts_in_time, cnts):
• score = (100/ cnts) * cnts_in_time
• return round(score, 2)
• supplier_score_dict = dict([(supplier, calc_score(cnt_in_time(supplier), cnt_occ(supplier))) for supplier in distinct_suppliers])
• # result: {'Supplier 2234': 50.0, 'Supplier 2448': 100.0}
• print(supplier_score_dict)
• result_file = 'result.json'
• with open(result_file, 'w') as f:
• json.dump(supplier_score_dict, f)

Graph