Enhance salary analytics API with database operations and performance logging

- Introduced `DatabaseOperations` class for managing batch results in the database.
- Added functionality to create a batch results table and save batch processing results.
- Updated API endpoints to log execution time and handle batch processing errors more effectively.
- Improved response handling in analysis endpoints and added batch metadata to results.
- Suppressed warnings and improved logging throughout the application.

salary_analytics/salary_earner_analyzer.py

@@ -6,8 +6,16 @@ import pandas as pd
 import matplotlib.pyplot as plt
 from matplotlib_venn import venn3
 from datetime import datetime, timedelta
+import logging
 from .config import MODEL_CONFIG, OUTPUT_PATHS
 
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
 class SalaryEarnerAnalyzer:
     def __init__(self, df):
         self.df = df
@@ -124,7 +132,7 @@ class SalaryEarnerAnalyzer:
 
         # Generate final table
         self.final_table = self.generate_salary_earners_table(all_three_hypotheses)
-        print(f"Found {self.final_table['accountid'].nunique()} verified salary earners")
+        logger.info(f"Found {self.final_table['accountid'].nunique()} verified salary earners")
 
         # Generate likely salary earner table
         green_section = self.filter_venn_section(
@@ -142,11 +150,11 @@ class SalaryEarnerAnalyzer:
         self.likely_salary_earner = pd.concat([yellow_section, green_section])
         self.likely_salary_earner = self.likely_salary_earner.drop_duplicates(subset=['id'])
         self.likely_salary_earner = self.generate_salary_earners_table(self.likely_salary_earner)
-        print(f"Found {self.likely_salary_earner['accountid'].nunique()} likely salary earners")
+        logger.info(f"Found {self.likely_salary_earner['accountid'].nunique()} likely salary earners")
 
         # Analyze high earners
         self.high_earner_details, total_high_earners = self.analyze_salary_earners(self.final_table)
-        print(f"\nTotal High Earners: {total_high_earners}")
+        logger.info(f"\nTotal High Earners: {total_high_earners}")
 
         # Plot hypothesis overlap
         self.plot_hypothesis_overlap(