| import json |
| import pandas as pd |
| import os |
| from neo4j import GraphDatabase |
|
|
| |
| NEO4J_URI = os.environ.get("NEO4J_URI") |
| NEO4J_USER = os.environ.get("NEO4J_USER") |
| NEO4J_PASS = os.environ.get("NEO4J_PASS") |
|
|
| _driver=None |
|
|
| def get_driver(): |
| global _driver |
| if _driver is None: |
| _driver = GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASS)) |
| return _driver |
|
|
| |
| eligibility_df = pd.read_csv("cards_eligibility_updated.csv") |
| card_to_bank = dict(zip(eligibility_df['Name'], eligibility_df['Bank'])) |
|
|
| |
| df = pd.read_csv("credit_card_data_updated.csv") |
| card_descriptions = dict(zip(df["name"], df["description"])) |
|
|
| |
| df_all_cards = pd.read_csv("credit_card_data_updated.csv") |
| all_card_names = df_all_cards["name"].tolist() |
| all_card_lookup = dict(zip(df_all_cards["name"], df_all_cards["description"])) |
| |
| with open('for_graph_construction_(expanded labels).json') as f: |
| card_feature_data = json.load(f) |
|
|
| card_features_lookup = { |
| card['card_name']: set(card['features']) |
| for card in card_feature_data |
| } |
|
|
|
|
| |
| eligibility_lookup = {} |
| for _, row in eligibility_df.iterrows(): |
| card_name = row["Name"].strip() |
| eligibility_info = f""" |
| - Bank: {row['Bank']} |
| - Age: {row['Minimum Age']} to {row['Maximum Age']} |
| - Minimum Income: {row['Minimum Income (LPA)']} LPA |
| - Minimum Credit Score: {row['Minimum Credit Score']} |
| - Joining Fee: ₹{row['Joining fee']} |
| - Annual Fee: ₹{row['Annual fee']} |
| """ |
| eligibility_lookup[card_name] = eligibility_info.strip() |
|
|
| |
| def get_all_features(): |
| with get_driver().session() as session: |
| result = session.run("MATCH (f:Feature) RETURN f.name AS feature") |
| return [record["feature"] for record in result] |
|
|
| features = get_all_features() |
|
|
