[add]: refactoring and cleanup

app/models/batch_results.py

@@ -0,0 +1,97 @@
+from sqlalchemy import Column, Integer, String, DateTime, Numeric, Boolean, func
+from sqlalchemy.orm import declarative_base, Session
+from datetime import datetime
+from app.utils.logger import logger
+from app.extensions import db
+
+
+class BatchResult(db.Model):
+    __tablename__ = "salary_analytics_batch_results"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    batch_number = Column(Integer, nullable=False)
+    total_batches = Column(Integer, nullable=False)
+    processed_at = Column(DateTime, default=datetime.utcnow)
+    accountid = Column(String, nullable=False)
+    num_months = Column(Integer)
+    least_inflow_6m = Column(Numeric)
+    avg_monthly_salary = Column(Numeric)
+    estimated_next_amount = Column(Numeric)
+    estimated_next_date = Column(DateTime)
+    is_45day_salary = Column(Boolean, default=False)
+    is_2months_salary = Column(Boolean, default=False)
+    status = Column(String, default="success")
+
+
+    @classmethod
+    def save_batch(cls, session: Session, batch_number, total_batches, results_df, status="success"):
+        """Save batch results into DB using ORM bulk insert."""
+        try:
+            results_df["batch_number"] = batch_number
+            results_df["total_batches"] = total_batches
+            results_df["processed_at"] = datetime.utcnow()
+            results_df["status"] = status
+
+            # Normalize boolean columns
+            results_df["is_45day_salary"] = results_df.get("45daysalary", False)
+            results_df["is_2months_salary"] = results_df.get("2monthssalary", False)
+
+            # Convert to list of ORM objects
+            records = [
+                cls(**row)
+                for row in results_df.to_dict("records")
+            ]
+
+            session.bulk_save_objects(records)
+            session.commit()
+            logger.info(f"Saved batch {batch_number} successfully.")
+            return True
+        except Exception as e:
+            session.rollback()
+            logger.error(f"Error saving batch {batch_number}: {str(e)}")
+            return False
+
+    @classmethod
+    def get_batch_status(cls, session: Session, batch_number: int):
+        """Return summary info about one batch."""
+        try:
+            result = (
+                session.query(
+                    cls.batch_number,
+                    cls.total_batches,
+                    cls.processed_at,
+                    func.count().label("total_records"),
+                    func.sum(func.case((cls.status == "success", 1), else_=0)).label("successful_records"),
+                    func.sum(func.case((cls.status == "error", 1), else_=0)).label("failed_records"),
+                )
+                .filter(cls.batch_number == batch_number)
+                .group_by(cls.batch_number, cls.total_batches, cls.processed_at)
+                .order_by(cls.processed_at.desc())
+                .first()
+            )
+            return dict(result._mapping) if result else None
+        except Exception as e:
+            logger.error(f"Error fetching batch {batch_number} status: {str(e)}")
+            return None
+
+    @classmethod
+    def get_all_batches(cls, session: Session):
+        """Return summaries for all batches."""
+        try:
+            results = (
+                session.query(
+                    cls.batch_number,
+                    cls.total_batches,
+                    cls.processed_at,
+                    func.count().label("total_records"),
+                    func.sum(func.case((cls.status == "success", 1), else_=0)).label("successful_records"),
+                    func.sum(func.case((cls.status == "error", 1), else_=0)).label("failed_records"),
+                )
+                .group_by(cls.batch_number, cls.total_batches, cls.processed_at)
+                .order_by(cls.batch_number)
+                .all()
+            )
+            return [dict(r._mapping) for r in results]
+        except Exception as e:
+            logger.error(f"Error fetching all batches: {str(e)}")
+            return []