from fastapi import APIRouter, HTTPException
import pandas as pd
from database import fetch_data
from utils.data_processing import preprocess_data
from logger import logger

# Initialize router
router = APIRouter()

def get_filtered_data(columns):
    """Fetches and filters data based on required columns."""
    try:
        raw_data = fetch_data()
        df = preprocess_data(pd.DataFrame(raw_data))
        missing_cols = [col for col in columns if col not in df.columns]
        if missing_cols:
            raise HTTPException(status_code=400, detail=f"Missing columns: {missing_cols}")
        return df[columns].dropna()
    except Exception as e:
        logger.error(f"Error fetching data: {e}")
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/satisfaction-analysis")
def satisfaction_analysis():
    try:
        data = get_filtered_data(['Satisfaction Score', 'DepartmentType'])
        result = data.groupby("DepartmentType")["Satisfaction Score"].mean().reset_index()
        return result.to_dict(orient="records")
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/department-performance")
def department_performance():
    try:
        data = get_filtered_data(["Performance Score", "Current Employee Rating", "DepartmentType"])
        result = data.groupby("DepartmentType")[["Performance Score", "Current Employee Rating"]].mean().reset_index()
        return result.to_dict(orient="records")
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/training-analytics")
def training_analytics():
    try:
        data = get_filtered_data(['Training Outcome', 'Training Cost'])
        completion_rates = data.groupby("Training Cost")['Training Outcome'].value_counts(normalize=True).unstack(fill_value=0)
        return completion_rates.to_dict()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/engagement-performance-correlation")
def engagement_performance_correlation():
    try:
        data = get_filtered_data(['Engagement Score', 'Performance Score'])
        correlation = data[['Engagement Score', 'Performance Score']].corr().iloc[0, 1]
        return {"correlation_coefficient": correlation}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/cost-benefit-analysis")
def cost_benefit_analysis():
    try:
        data = get_filtered_data(['Training Cost', 'Performance Score', 'DepartmentType'])
        result = data.groupby("DepartmentType").apply(lambda g: g["Performance Score"].mean() / g["Training Cost"].sum()).reset_index(name="ROI")
        return result.to_dict(orient="records")
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/training-effectiveness")
def training_effectiveness():
    try:
        data = get_filtered_data(['Training Outcome', 'Performance Score', 'Training Program Name'])
        result = data.groupby("Training Program Name")["Performance Score"].mean().reset_index()
        return result.to_dict(orient="records")
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/diversity-dashboard")
def diversity_dashboard():
    try:
        data = get_filtered_data(['GenderCode', 'RaceDesc', 'DepartmentType'])
        diversity_metrics = data.groupby("DepartmentType")['GenderCode'].value_counts(normalize=True).unstack(fill_value=0)
        return diversity_metrics.to_dict()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/worklife-balance-impact")
def worklife_balance_impact():
    try:
        data = get_filtered_data(['Work-Life Balance Score', 'Performance Score'])
        correlation = data[['Work-Life Balance Score', 'Performance Score']].corr().iloc[0, 1]
        return {"correlation_coefficient": correlation}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")

@router.get("/career-development")
def career_development():
    try:
        data = get_filtered_data(['Employee ID', 'StartDate'])
        career_progress = data.groupby("Employee ID")["StartDate"].count().reset_index(name="Career Movements")
        return career_progress.to_dict(orient="records")
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {e}")