salakojoshua1234_gmail.com
332b743fa5
Updated config.py to include the salary detection endpoint, headers, and sample payloads. Enhanced salary_detect.py to utilize the new configuration for making POST requests to the endpoint with random salary data. Improved error handling during the request process.
97 lines
3.8 KiB
Python
97 lines
3.8 KiB
Python
"""
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Configuration settings for the salary analytics package.
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"""
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import os
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from dotenv import load_dotenv
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import random
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# Load environment variables
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load_dotenv()
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# Base directories
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BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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OUTPUT_DIR = os.path.join(BASE_DIR, "output")
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PLOTS_DIR = os.path.join(OUTPUT_DIR, "plots")
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CSV_DIR = os.path.join(OUTPUT_DIR, "csv")
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MODEL_DIR = os.path.join(OUTPUT_DIR, "models")
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# Create directories if they don't exist
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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os.makedirs(PLOTS_DIR, exist_ok=True)
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os.makedirs(CSV_DIR, exist_ok=True)
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os.makedirs(MODEL_DIR, exist_ok=True)
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# Database Configuration
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DB_CONFIG = {
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"user": os.getenv("DB_USER"), # Default value as fallback
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"password": os.getenv("DB_PASSWORD"),
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"name": os.getenv("DB_NAME"),
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"port": os.getenv("DB_PORT"),
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"host": os.getenv("DB_HOST")
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}
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# SQLAlchemy Configuration
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SQLALCHEMY_DATABASE_URI = (
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f"postgresql://{DB_CONFIG['user']}:{DB_CONFIG['password']}@"
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f"{DB_CONFIG['host']}:{DB_CONFIG['port']}/{DB_CONFIG['name']}"
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)
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SQLALCHEMY_TRACK_MODIFICATIONS = False
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# Table Configuration
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TABLE_NAME = "customer_account_transaction_hx"
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BATCH_RESULTS_TABLE = "salary_analytics_batch_results"
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# Salary Keywords
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SALARY_KEYWORDS = [
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"salary", "payroll", "income", "wage", "wages",
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"earnings", "earning", "monthly pay", "net pay", "gross pay", "compensation",
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"monthlypay", "netpay", "grosspay",
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"remuneration", "stipend", "allowance", "bonus", "commission",
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"pension", "retirement", "dividend", "benefits", "reimbursement",
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"overtime", "incentive", "paycheck", "paycheque", "salary advance",
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"monthly income", "income tax refund", "employer deposit",
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"payroll deposit", "salary credit", "income credit", "salary transfer",
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"income transfer", "salary received", "income received", "hr deposit",
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"company deposit", "employer payment", "employee payment",
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"sal",
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]
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# Model Configuration
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MODEL_CONFIG = {
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"cv_threshold": 0.10,
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"min_transactions": 3,
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"threshold": 0.7,
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"high_earner_threshold": 10000
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}
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# File Paths
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OUTPUT_PATHS = {
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"high_earner_details": os.path.join(CSV_DIR, "high_earner_details.csv"),
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"likely_salary_earner": os.path.join(CSV_DIR, "likely_salary_earner.csv"),
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"final_table": os.path.join(CSV_DIR, "final_table.csv"),
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"consistent_earners_plot": os.path.join(PLOTS_DIR, "consistent_earners_predictions.png"),
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"inconsistent_earners_plot": os.path.join(PLOTS_DIR, "inconsistent_earners_predictions.png"),
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"hypothesis_overlap_plot": os.path.join(PLOTS_DIR, "hypothesis_overlap.png"),
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"consistent_model": os.path.join(MODEL_DIR, "consistent_model.joblib"),
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"inconsistent_model": os.path.join(MODEL_DIR, "inconsistent_model.joblib"),
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"consistent_scaler": os.path.join(MODEL_DIR, "consistent_scaler.joblib"),
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"inconsistent_scaler": os.path.join(MODEL_DIR, "inconsistent_scaler.joblib")
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}
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# Salary Detect Endpoint Config
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SALARY_DETECT_URL = "http://www.simbrellang.net:5000/autocall/analytic-salary-detect"
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SALARY_DETECT_HEADERS = {
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"accept": "/",
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"Content-Type": "application/json"
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}
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SALARY_DETECT_PAYLOADS = [
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{"salaryDate": "2022-01-01", "customerId": "CN621868", "accountId": "2017821799", "salaryAmount": 200000},
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{"customerId": "CUC2268333011", "accountId": "ACC8116931898", "salaryDate": "2025-07-08", "salaryAmount": 200000},
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{"customerId": "CUC2163677018", "accountId": "ACC8118539484", "salaryDate": "2025-07-08", "salaryAmount": 200000},
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{"customerId": "CUC1968062010", "accountId": "ACC8115473093", "salaryDate": "2025-07-08", "salaryAmount": 200000},
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{"customerId": "CUC1302360013", "accountId": "ACC8117628489", "salaryDate": "2025-07-08", "salaryAmount": 200000}
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]
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def get_random_salary_payload():
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return [random.choice(SALARY_DETECT_PAYLOADS)] |