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digifi-Analytics/salary_analytics/db_operations.py
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CHIEFSOFT\ameye e869785624 first commit
2025-05-17 03:52:41 -04:00

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Python

"""
Database operations module for salary analytics.
"""
import logging
from sqlalchemy import text
from .config import BATCH_RESULTS_TABLE
from datetime import datetime
logger = logging.getLogger(__name__)
class DatabaseOperations:
def __init__(self, engine):
"""Initialize with SQLAlchemy engine."""
self.engine = engine
def create_batch_results_table(self):
"""Create the batch results table if it doesn't exist."""
try:
with self.engine.connect() as conn:
# Check if table exists
check_table = text(f"SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = '{BATCH_RESULTS_TABLE}')")
table_exists = conn.execute(check_table).scalar()
if not table_exists:
# Create table
create_table = text(f"""
CREATE TABLE {BATCH_RESULTS_TABLE} (
id SERIAL PRIMARY KEY,
batch_number INTEGER,
total_batches INTEGER,
processed_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
accountid TEXT,
num_months INTEGER,
least_inflow_6m DECIMAL,
avg_monthly_salary DECIMAL,
estimated_next_amount DECIMAL,
estimated_next_date DATE,
is_45day_salary BOOLEAN,
is_2months_salary BOOLEAN,
status TEXT
)
""")
conn.execute(create_table)
conn.commit()
logger.info(f"Created table {BATCH_RESULTS_TABLE}")
return True
except Exception as e:
logger.error(f"Error creating batch results table: {str(e)}")
return False
def save_batch_to_db(self, batch_number, total_batches, results_df, status="success"):
"""Save batch processing results to database."""
try:
with self.engine.connect() as conn:
# Add batch metadata to the DataFrame
results_df['batch_number'] = batch_number
results_df['total_batches'] = total_batches
results_df['processed_at'] = datetime.now()
# Convert DataFrame to list of dictionaries
records = results_df.to_dict('records')
# Insert each record
for record in records:
insert_query = text(f"""
INSERT INTO {BATCH_RESULTS_TABLE}
(batch_number, total_batches, processed_at, accountid, num_months,
least_inflow_6m, avg_monthly_salary, estimated_next_amount,
estimated_next_date, is_45day_salary, is_2months_salary, status)
VALUES
(:batch_number, :total_batches, :processed_at, :accountid, :num_months,
:least_inflow_6m, :avg_monthly_salary, :estimated_next_amount,
:estimated_next_date, :is_45day_salary, :is_2months_salary, :status)
""")
# Convert boolean columns to proper format
record['is_45day_salary'] = record.get('45daysalary', False)
record['is_2months_salary'] = record.get('2monthssalary', False)
# Add status
record['status'] = status
conn.execute(insert_query, record)
conn.commit()
logger.info(f"Successfully saved batch {batch_number} results to database")
return True
except Exception as e:
logger.error(f"Error saving batch {batch_number} to database: {str(e)}")
return False
def get_batch_status(self, batch_number):
"""Get the status of a specific batch."""
try:
with self.engine.connect() as conn:
query = text(f"""
SELECT
batch_number,
total_batches,
processed_at,
COUNT(*) as total_records,
SUM(CASE WHEN status = 'success' THEN 1 ELSE 0 END) as successful_records,
SUM(CASE WHEN status = 'error' THEN 1 ELSE 0 END) as failed_records
FROM {BATCH_RESULTS_TABLE}
WHERE batch_number = :batch_number
GROUP BY batch_number, total_batches, processed_at
ORDER BY processed_at DESC
LIMIT 1
""")
result = conn.execute(query, {"batch_number": batch_number}).fetchone()
return dict(result) if result else None
except Exception as e:
logger.error(f"Error getting batch {batch_number} status: {str(e)}")
return None
def get_all_batches(self):
"""Get all batch processing results."""
try:
with self.engine.connect() as conn:
query = text(f"""
SELECT
batch_number,
total_batches,
processed_at,
COUNT(*) as total_records,
SUM(CASE WHEN status = 'success' THEN 1 ELSE 0 END) as successful_records,
SUM(CASE WHEN status = 'error' THEN 1 ELSE 0 END) as failed_records
FROM {BATCH_RESULTS_TABLE}
GROUP BY batch_number, total_batches, processed_at
ORDER BY batch_number
""")
results = conn.execute(query).fetchall()
return [dict(row) for row in results]
except Exception as e:
logger.error(f"Error getting all batches: {str(e)}")
return []