Poll-system/app/internal/handlers/admin_reports.go

package handlers

import (
	"fmt"
	"log"
	"net/http"
	"strconv"
	"strings"
	"time"

	"github.com/patel-mann/poll-system/app/internal/models"
	"github.com/patel-mann/poll-system/app/internal/utils"
)

type ReportResult struct {
	Columns []string        `json:"columns"`
	Rows    [][]interface{} `json:"rows"`
	Count   int             `json:"count"`
	Error   string          `json:"error,omitempty"`
}

type ReportDefinition struct {
	ID          string `json:"id"`
	Name        string `json:"name"`
	Description string `json:"description"`
	SQL         string `json:"-"` // Don't expose SQL in JSON
}

type SummaryStats struct {
	Label string `json:"label"`
	Value string `json:"value"`
}

// Simple Reports Handler
func ReportsHandler(w http.ResponseWriter, r *http.Request) {
	username, _ := models.GetCurrentUserName(r)
	role := r.Context().Value("user_role").(int)

	if role != 1 {
		http.Error(w, "Unauthorized", http.StatusForbidden)
		return
	}

	category := r.URL.Query().Get("category")
	reportID := r.URL.Query().Get("report")
	dateFrom := r.URL.Query().Get("date_from")
	dateTo := r.URL.Query().Get("date_to")
	export := r.URL.Query().Get("export")

	// Set default date range if not provided
	if dateFrom == "" {
		dateFrom = time.Now().AddDate(0, 0, -30).Format("2006-01-02")
	}
	if dateTo == "" {
		dateTo = time.Now().Format("2006-01-02")
	}

	var result ReportResult
	var reportTitle, reportDescription string

	// Generate report if both category and report are selected
	if category != "" && reportID != "" {
		result, reportTitle, reportDescription = executeReport(category, reportID, dateFrom, dateTo)
		
		// Handle CSV export
		if export == "csv" {
			exportCSV(w, result, reportTitle)
			return
		}
	}

	utils.Render(w, "reports.html", map[string]interface{}{
		"Title":             "Campaign Reports",
		"IsAuthenticated":   true,
		"ShowAdminNav":      role == 1,
		"ShowVolunteerNav":  role != 1,
		"UserName":          username,
		"ActiveSection":  	 "reports",
		"Category":          category,
		"ReportID":          reportID,
		"DateFrom":          dateFrom,
		"DateTo":            dateTo,
		"AvailableReports":  getReportsForCategory(category),
		"Result":            result,
		"ReportTitle":       reportTitle,
		"ReportDescription": reportDescription,
		"GeneratedAt":       time.Now().Format("January 2, 2006 at 3:04 PM"),
		"SummaryStats":      generateSummaryStats(result),
	})
}

// Execute a specific report
func executeReport(category, reportID, dateFrom, dateTo string) (ReportResult, string, string) {
	report := getReportDefinition(category, reportID)
	if report == nil {
		return ReportResult{Error: "Report not found"}, "", ""
	}

	// Replace date placeholders in SQL
	sql := report.SQL
	sql = replaceDatePlaceholders(sql, dateFrom, dateTo)

	// Execute the SQL query
	rows, err := models.DB.Query(sql)
	if err != nil {
		log.Printf("Report SQL error: %v", err)
		return ReportResult{Error: "Failed to execute report"}, report.Name, report.Description
	}
	defer rows.Close()

	// Get column names
	columns, err := rows.Columns()
	if err != nil {
		return ReportResult{Error: "Failed to get columns"}, report.Name, report.Description
	}

	// Process rows
	var results [][]interface{}
	for rows.Next() {
		values := make([]interface{}, len(columns))
		valuePtrs := make([]interface{}, len(columns))
		for i := range values {
			valuePtrs[i] = &values[i]
		}

		if err := rows.Scan(valuePtrs...); err != nil {
			continue
		}

		row := make([]interface{}, len(columns))
		for i, val := range values {
			if val == nil {
				row[i] = ""
			} else {
				switch v := val.(type) {
				case []byte:
					row[i] = string(v)
				case time.Time:
					row[i] = v.Format("2006-01-02 15:04:05")
				default:
					row[i] = fmt.Sprintf("%v", v)
				}
			}
		}
		results = append(results, row)
	}

	return ReportResult{
		Columns: columns,
		Rows:    results,
		Count:   len(results),
	}, report.Name, report.Description
}

// Get available reports for a category
func getReportsForCategory(category string) []ReportDefinition {
	allReports := getAllReportDefinitions()
	if reports, exists := allReports[category]; exists {
		return reports
	}
	return []ReportDefinition{}
}

// Get a specific report definition
func getReportDefinition(category, reportID string) *ReportDefinition {
	reports := getReportsForCategory(category)
	for _, report := range reports {
		if report.ID == reportID {
			return &report
		}
	}
	return nil
}

// Define all available reports
func getAllReportDefinitions() map[string][]ReportDefinition {
	return map[string][]ReportDefinition{
		"users": {
			{
				ID:          "volunteer_participation_rate",
				Name:        "Volunteer Participation Rate",
				Description: "Poll responses and donations collected by each volunteer/team lead",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					u.email,
					r.name as role,
					COUNT(DISTINCT p.poll_id) as polls_created,
					COUNT(DISTINCT pr.poll_response_id) as responses_collected,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					COUNT(DISTINCT a.sched_id) as appointments_scheduled
				FROM users u
				JOIN role r ON u.role_id = r.role_id
				LEFT JOIN poll p ON u.user_id = p.user_id AND p.created_at BETWEEN ?1 AND ?2
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				LEFT JOIN appointment a ON u.user_id = a.user_id AND a.created_at BETWEEN ?1 AND ?2
				WHERE u.role_id IN (2, 3)
				GROUP BY u.user_id, u.first_name, u.last_name, u.email, r.name
				ORDER BY responses_collected DESC, total_donations DESC`,
			},
			{
				ID:          "top_performing_volunteers",
				Name:        "Top-Performing Volunteers & Team Leads",
				Description: "Volunteers ranked by responses collected and donations secured",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					r.name as role,
					COUNT(DISTINCT pr.poll_response_id) as responses_collected,
					COALESCE(SUM(pr.question6_donation_amount), 0) as donations_secured,
					COUNT(DISTINCT p.poll_id) as polls_created,
					AVG(pr.question6_donation_amount) as avg_donation_per_poll
				FROM users u
				JOIN role r ON u.role_id = r.role_id
				JOIN poll p ON u.user_id = p.user_id
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE u.role_id IN (2, 3) AND p.created_at BETWEEN ?1 AND ?2
				GROUP BY u.user_id, u.first_name, u.last_name, r.name
				HAVING COUNT(DISTINCT pr.poll_response_id) > 0
				ORDER BY responses_collected DESC, donations_secured DESC
				LIMIT 20`,
			},
			{
				ID:          "response_donation_ratio",
				Name:        "Response-to-Donation Ratio per Volunteer",
				Description: "Efficiency measure showing donation amount per response collected",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					COUNT(DISTINCT pr.poll_response_id) as total_responses,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					CASE 
						WHEN COUNT(DISTINCT pr.poll_response_id) > 0 
						THEN COALESCE(SUM(pr.question6_donation_amount), 0) / COUNT(DISTINCT pr.poll_response_id)
						ELSE 0 
					END as donation_per_response,
					CASE 
						WHEN COALESCE(SUM(pr.question6_donation_amount), 0) > 0 
						THEN COUNT(DISTINCT pr.poll_response_id) / COALESCE(SUM(pr.question6_donation_amount), 1)
						ELSE COUNT(DISTINCT pr.poll_response_id)
					END as responses_per_dollar
				FROM users u
				JOIN poll p ON u.user_id = p.user_id
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE u.role_id IN (2, 3) AND p.created_at BETWEEN ?1 AND ?2
				GROUP BY u.user_id, u.first_name, u.last_name
				HAVING COUNT(DISTINCT pr.poll_response_id) > 0
				ORDER BY donation_per_response DESC`,
			},
			{
				ID:          "user_address_coverage",
				Name:        "User Address Coverage",
				Description: "Number of unique addresses covered by each volunteer/team lead",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					COUNT(DISTINCT p.address_id) as unique_addresses_polled,
					COUNT(DISTINCT a.address_id) as unique_addresses_appointed,
					COUNT(DISTINCT COALESCE(p.address_id, a.address_id)) as total_unique_addresses,
					COUNT(DISTINCT pr.poll_response_id) as total_responses
				FROM users u
				LEFT JOIN poll p ON u.user_id = p.user_id AND p.created_at BETWEEN ?1 AND ?2
				LEFT JOIN appointment a ON u.user_id = a.user_id AND a.created_at BETWEEN ?1 AND ?2
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE u.role_id IN (2, 3)
				GROUP BY u.user_id, u.first_name, u.last_name
				HAVING COUNT(DISTINCT COALESCE(p.address_id, a.address_id)) > 0
				ORDER BY total_unique_addresses DESC, total_responses DESC`,
			},
		},
		"addresses": {
			{
				ID:          "poll_responses_by_address",
				Name:        "Total Poll Responses by Address",
				Description: "Shows engagement hotspots - addresses with most poll responses",
				SQL: `SELECT 
					ad.address,
					ad.postal_code,
					ad.street_quadrant,
					COUNT(DISTINCT pr.poll_response_id) as total_responses,
					COUNT(DISTINCT p.poll_id) as polls_conducted,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					CASE 
						WHEN COUNT(DISTINCT pr.poll_response_id) > 0 
						THEN COALESCE(SUM(pr.question6_donation_amount), 0) / COUNT(DISTINCT pr.poll_response_id)
						ELSE 0 
					END as avg_donation_per_response
				FROM address_database ad
				JOIN poll p ON ad.address_id = p.address_id
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2
				GROUP BY ad.address_id, ad.address, ad.postal_code, ad.street_quadrant
				ORDER BY total_responses DESC, total_donations DESC
				LIMIT 50`,
			},
			{
				ID:          "donations_by_address",
				Name:        "Total Donations by Address",
				Description: "Shows financially supportive areas - addresses with highest donations",
				SQL: `SELECT 
					ad.address,
					ad.postal_code,
					ad.street_quadrant,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					COUNT(DISTINCT p.poll_id) as polls_conducted,
					COUNT(DISTINCT pr.poll_response_id) as total_responses,
					AVG(pr.question6_donation_amount) as avg_donation_per_poll
				FROM address_database ad
				JOIN poll p ON ad.address_id = p.address_id
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2 AND pr.question6_donation_amount > 0
				GROUP BY ad.address_id, ad.address, ad.postal_code, ad.street_quadrant
				ORDER BY total_donations DESC
				LIMIT 50`,
			},
			{
				ID:          "street_level_breakdown",
				Name:        "Street-Level Breakdown (Responses & Donations)",
				Description: "Granular view for targeting - responses and donations by street",
				SQL: `SELECT 
					ad.street_name,
					ad.street_type,
					ad.street_quadrant,
					COUNT(DISTINCT ad.address_id) as unique_addresses,
					COUNT(DISTINCT pr.poll_response_id) as total_responses,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					COUNT(DISTINCT p.poll_id) as polls_conducted
				FROM address_database ad
				LEFT JOIN poll p ON ad.address_id = p.address_id AND p.created_at BETWEEN ?1 AND ?2
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE ad.street_name IS NOT NULL
				GROUP BY ad.street_name, ad.street_type, ad.street_quadrant
				HAVING COUNT(DISTINCT pr.poll_response_id) > 0 OR COALESCE(SUM(pr.question6_donation_amount), 0) > 0
				ORDER BY total_responses DESC, total_donations DESC`,
			},
			{
				ID:          "quadrant_summary",
				Name:        "Quadrant-Level Summary (NE, NW, SE, SW)",
				Description: "Higher-level trend view by city quadrants",
				SQL: `SELECT 
					COALESCE(ad.street_quadrant, 'Unknown') as quadrant,
					COUNT(DISTINCT ad.address_id) as unique_addresses,
					COUNT(DISTINCT p.poll_id) as polls_conducted,
					COUNT(DISTINCT pr.poll_response_id) as total_responses,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					AVG(pr.question6_donation_amount) as avg_donation_per_poll,
					COUNT(DISTINCT a.sched_id) as appointments_scheduled
				FROM address_database ad
				LEFT JOIN poll p ON ad.address_id = p.address_id AND p.created_at BETWEEN ?1 AND ?2
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				LEFT JOIN appointment a ON ad.address_id = a.address_id AND a.created_at BETWEEN ?1 AND ?2
				GROUP BY ad.street_quadrant
				ORDER BY total_responses DESC, total_donations DESC`,
			},
		},
		"appointments": {
			{
				ID:          "upcoming_appointments",
				Name:        "Upcoming Appointments per Volunteer/Team Lead",
				Description: "Scheduling load - upcoming appointments by user",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					r.name as role,
					COUNT(*) as upcoming_appointments,
					MIN(a.appointment_date) as earliest_appointment,
					MAX(a.appointment_date) as latest_appointment,
					COUNT(CASE WHEN a.appointment_date = CURRENT_DATE THEN 1 END) as today_appointments,
					COUNT(CASE WHEN a.appointment_date BETWEEN CURRENT_DATE AND CURRENT_DATE + INTERVAL '7 days' THEN 1 END) as week_appointments
				FROM appointment a
				JOIN users u ON a.user_id = u.user_id
				JOIN role r ON u.role_id = r.role_id
				WHERE a.appointment_date >= CURRENT_DATE AND a.appointment_date BETWEEN ?1 AND ?2
				GROUP BY u.user_id, u.first_name, u.last_name, r.name
				ORDER BY upcoming_appointments DESC`,
			},
			{
				ID:          "missed_vs_completed",
				Name:        "Missed vs Completed Appointments",
				Description: "Reliability metric - appointment completion rates",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					COUNT(*) as total_appointments,
					COUNT(CASE WHEN a.appointment_date < CURRENT_DATE THEN 1 END) as past_appointments,
					COUNT(CASE WHEN a.appointment_date >= CURRENT_DATE THEN 1 END) as upcoming_appointments,
					COUNT(CASE WHEN a.appointment_date < CURRENT_DATE AND EXISTS (
						SELECT 1 FROM poll p WHERE p.user_id = a.user_id AND p.address_id = a.address_id 
						AND DATE(p.created_at) = a.appointment_date
					) THEN 1 END) as completed_appointments,
					COUNT(CASE WHEN a.appointment_date < CURRENT_DATE AND NOT EXISTS (
						SELECT 1 FROM poll p WHERE p.user_id = a.user_id AND p.address_id = a.address_id 
						AND DATE(p.created_at) = a.appointment_date
					) THEN 1 END) as missed_appointments,
					CASE 
						WHEN COUNT(CASE WHEN a.appointment_date < CURRENT_DATE THEN 1 END) > 0
						THEN COUNT(CASE WHEN a.appointment_date < CURRENT_DATE AND EXISTS (
							SELECT 1 FROM poll p WHERE p.user_id = a.user_id AND p.address_id = a.address_id 
							AND DATE(p.created_at) = a.appointment_date
						) THEN 1 END) * 100.0 / COUNT(CASE WHEN a.appointment_date < CURRENT_DATE THEN 1 END)
						ELSE 0
					END as completion_rate_percent
				FROM appointment a
				JOIN users u ON a.user_id = u.user_id
				WHERE a.created_at BETWEEN ?1 AND ?2
				GROUP BY u.user_id, u.first_name, u.last_name
				ORDER BY completion_rate_percent DESC, total_appointments DESC`,
			},
			{
				ID:          "appointments_by_quadrant",
				Name:        "Appointments by Quadrant/Region",
				Description: "Geographic distribution of appointments",
				SQL: `SELECT 
					COALESCE(ad.street_quadrant, 'Unknown') as quadrant,
					COUNT(*) as total_appointments,
					COUNT(CASE WHEN a.appointment_date >= CURRENT_DATE THEN 1 END) as upcoming,
					COUNT(CASE WHEN a.appointment_date < CURRENT_DATE THEN 1 END) as past,
					COUNT(DISTINCT a.user_id) as unique_volunteers,
					COUNT(DISTINCT a.address_id) as unique_addresses
				FROM appointment a
				JOIN address_database ad ON a.address_id = ad.address_id
				WHERE a.created_at BETWEEN ?1 AND ?2
				GROUP BY ad.street_quadrant
				ORDER BY total_appointments DESC`,
			},
			{
				ID:          "scheduling_lead_time",
				Name:        "Average Lead Time (Scheduled vs Actual Date)",
				Description: "Scheduling efficiency - time between scheduling and appointment",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					COUNT(*) as total_appointments,
					AVG(a.appointment_date - DATE(a.created_at)) as avg_lead_time_days,
					MIN(a.appointment_date - DATE(a.created_at)) as min_lead_time_days,
					MAX(a.appointment_date - DATE(a.created_at)) as max_lead_time_days,
					COUNT(CASE WHEN a.appointment_date - DATE(a.created_at) < 1 THEN 1 END) as same_day_appointments,
					COUNT(CASE WHEN a.appointment_date - DATE(a.created_at) BETWEEN 1 AND 7 THEN 1 END) as week_ahead_appointments
				FROM appointment a
				JOIN users u ON a.user_id = u.user_id
				WHERE a.created_at BETWEEN ?1 AND ?2
				GROUP BY u.user_id, u.first_name, u.last_name
				HAVING COUNT(*) > 0
				ORDER BY avg_lead_time_days ASC`,
			},
		},
		"polls": {
			{
				ID:          "response_distribution",
				Name:        "Response Distribution (Yes/No/Neutral)",
				Description: "Outcome summary - distribution of poll responses",
				SQL: `SELECT 
					CASE 
						WHEN question1_voted_before = true AND question2_vote_again = true THEN 'Previous Voter - Will Vote Again'
						WHEN question1_voted_before = true AND question2_vote_again = false THEN 'Previous Voter - Will Not Vote Again'
						WHEN question1_voted_before = false AND question2_vote_again = true THEN 'New Voter - Will Vote'
						WHEN question1_voted_before = false AND question2_vote_again = false THEN 'New Voter - Will Not Vote'
						WHEN question1_voted_before IS NULL OR question2_vote_again IS NULL THEN 'Incomplete Response'
					END as response_category,
					COUNT(*) as response_count,
					COUNT(*) * 100.0 / (SELECT COUNT(*) FROM poll_response pr2 
						JOIN poll p2 ON pr2.poll_id = p2.poll_id 
						WHERE p2.created_at BETWEEN ?1 AND ?2) as percentage
				FROM poll_response pr
				JOIN poll p ON pr.poll_id = p.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2
				GROUP BY response_category
				ORDER BY response_count DESC`,
			},
			{
				ID:          "average_poll_response",
				Name:        "Average Poll Response (Yes/No %)",
				Description: "Overall sentiment - percentage breakdown of responses",
				SQL: `SELECT 
					'Previous Voters' as voter_type,
					COUNT(*) as total_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) as positive_responses,
					COUNT(CASE WHEN question2_vote_again = false THEN 1 END) as negative_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) * 100.0 / COUNT(*) as positive_percentage
				FROM poll_response pr
				JOIN poll p ON pr.poll_id = p.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2 AND question1_voted_before = true
				UNION ALL
				SELECT 
					'New Voters' as voter_type,
					COUNT(*) as total_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) as positive_responses,
					COUNT(CASE WHEN question2_vote_again = false THEN 1 END) as negative_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) * 100.0 / COUNT(*) as positive_percentage
				FROM poll_response pr
				JOIN poll p ON pr.poll_id = p.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2 AND question1_voted_before = false
				UNION ALL
				SELECT 
					'Overall' as voter_type,
					COUNT(*) as total_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) as positive_responses,
					COUNT(CASE WHEN question2_vote_again = false THEN 1 END) as negative_responses,
					COUNT(CASE WHEN question2_vote_again = true THEN 1 END) * 100.0 / COUNT(*) as positive_percentage
				FROM poll_response pr
				JOIN poll p ON pr.poll_id = p.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2`,
			},
			{
				ID:          "donations_by_poll",
				Name:        "Donations by Poll",
				Description: "Which polls drive donations - donation amounts per poll",
				SQL: `SELECT 
					p.poll_id,
					u.first_name || ' ' || u.last_name as creator_name,
					ad.address,
					pr.question6_donation_amount,
					COUNT(pr.poll_response_id) as response_count,
					CASE 
						WHEN COUNT(pr.poll_response_id) > 0 
						THEN pr.question6_donation_amount / COUNT(pr.poll_response_id)
						ELSE 0 
					END as donation_per_response,
					p.created_at as poll_date
				FROM poll p
				JOIN users u ON p.user_id = u.user_id
				JOIN address_database ad ON p.address_id = ad.address_id
				LEFT JOIN poll_response pr ON p.poll_id = pr.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2 AND pr.question6_donation_amount > 0
				GROUP BY p.poll_id, u.first_name, u.last_name, ad.address, pr.question6_donation_amount, p.created_at
				ORDER BY pr.question6_donation_amount DESC, response_count DESC`,
			},
			{
				ID:          "response_donation_correlation",
				Name:        "Response-to-Donation Correlation",
				Description: "Are positive responses linked to donations?",
				SQL: `SELECT 
					CASE 
						WHEN question2_vote_again = true THEN 'Will Vote Again'
						WHEN question2_vote_again = false THEN 'Will Not Vote Again'
						ELSE 'No Response'
					END as response_type,
					COUNT(*) as response_count,
					COUNT(CASE WHEN pr.question6_donation_amount > 0 THEN 1 END) as responses_with_donations,
					COALESCE(SUM(pr.question6_donation_amount), 0) as total_donations,
					AVG(pr.question6_donation_amount) as avg_donation,
					COUNT(CASE WHEN pr.question6_donation_amount > 0 THEN 1 END) * 100.0 / COUNT(*) as donation_rate_percent
				FROM poll_response pr
				JOIN poll p ON pr.poll_id = p.poll_id
				WHERE p.created_at BETWEEN ?1 AND ?2
				GROUP BY question2_vote_again
				ORDER BY total_donations DESC`,
			},
		},
		"availability": {
			{
				ID:          "volunteer_availability_schedule",
				Name:        "Volunteer Availability by Date Range",
				Description: "Who can work when - current volunteer availability schedules",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					u.email,
					av.day_of_week,
					av.start_time,
					av.end_time,
					EXTRACT(EPOCH FROM (av.end_time - av.start_time))/3600 as hours_available,
					av.created_at as schedule_updated
				FROM availability av
				JOIN users u ON av.user_id = u.user_id
				WHERE u.role_id IN (2, 3) AND av.created_at BETWEEN ?1 AND ?2
				ORDER BY u.first_name, u.last_name, 
					CASE av.day_of_week 
						WHEN 'Monday' THEN 1 
						WHEN 'Tuesday' THEN 2 
						WHEN 'Wednesday' THEN 3 
						WHEN 'Thursday' THEN 4 
						WHEN 'Friday' THEN 5 
						WHEN 'Saturday' THEN 6 
						WHEN 'Sunday' THEN 7 
					END, av.start_time`,
			},
			{
				ID:          "volunteer_fulfillment",
				Name:        "Volunteer Fulfillment (Available vs Actually Worked)",
				Description: "Reliability measure - comparing availability to actual appointments",
				SQL: `SELECT 
					u.first_name || ' ' || u.last_name as volunteer_name,
					COUNT(DISTINCT av.availability_id) as availability_slots,
					SUM(EXTRACT(EPOCH FROM (av.end_time - av.start_time))/3600) as total_hours_available,
					COUNT(DISTINCT a.sched_id) as appointments_scheduled,
					COUNT(DISTINCT CASE WHEN a.appointment_date < CURRENT_DATE THEN a.sched_id END) as past_appointments,
					COUNT(DISTINCT CASE WHEN a.appointment_date < CURRENT_DATE AND EXISTS (
						SELECT 1 FROM poll p WHERE p.user_id = a.user_id AND p.address_id = a.address_id 
						AND DATE(p.created_at) = a.appointment_date
					) THEN a.sched_id END) as completed_appointments,
					CASE 
						WHEN COUNT(DISTINCT CASE WHEN a.appointment_date < CURRENT_DATE THEN a.sched_id END) > 0
						THEN COUNT(DISTINCT CASE WHEN a.appointment_date < CURRENT_DATE AND EXISTS (
							SELECT 1 FROM poll p WHERE p.user_id = a.user_id AND p.address_id = a.address_id 
							AND DATE(p.created_at) = a.appointment_date
						) THEN a.sched_id END) * 100.0 / COUNT(DISTINCT CASE WHEN a.appointment_date < CURRENT_DATE THEN a.sched_id END)
						ELSE 0
					END as fulfillment_rate_percent
				FROM users u
				LEFT JOIN availability av ON u.user_id = av.user_id AND av.created_at BETWEEN ?1 AND ?2
				LEFT JOIN appointment a ON u.user_id = a.user_id AND a.created_at BETWEEN ?1 AND ?2
				WHERE u.role_id IN (2, 3)
				GROUP BY u.user_id, u.first_name, u.last_name
				HAVING COUNT(DISTINCT av.availability_id) > 0 OR COUNT(DISTINCT a.sched_id) > 0
				ORDER BY fulfillment_rate_percent DESC, total_hours_available DESC`,
			},
		},
	}
}

// Replace date placeholders in SQL
func replaceDatePlaceholders(sql, dateFrom, dateTo string) string {
	sql = strings.ReplaceAll(sql, "?1", "'"+dateFrom+"'")
	sql = strings.ReplaceAll(sql, "?2", "'"+dateTo+" 23:59:59'")
	return sql
}

// Generate summary statistics
func generateSummaryStats(result ReportResult) []SummaryStats {
	if len(result.Rows) == 0 {
		return nil
	}

	stats := []SummaryStats{
		{Label: "Total Records", Value: strconv.Itoa(result.Count)},
	}

	// Try to generate additional stats based on column types
	if len(result.Columns) > 0 {
		// Look for numeric columns to calculate sums/averages
		for colIdx, colName := range result.Columns {
			if strings.Contains(strings.ToLower(colName), "count") ||
				strings.Contains(strings.ToLower(colName), "total") ||
				strings.Contains(strings.ToLower(colName), "amount") {
				
				var sum float64
				var validCount int
				
				for _, row := range result.Rows {
					if colIdx < len(row) {
						if val, err := strconv.ParseFloat(fmt.Sprintf("%v", row[colIdx]), 64); err == nil {
							sum += val
							validCount++
						}
					}
				}
				
				if validCount > 0 {
					stats = append(stats, SummaryStats{
						Label: fmt.Sprintf("Total %s", strings.Title(strings.ToLower(colName))),
						Value: fmt.Sprintf("%.2f", sum),
					})
					
					if validCount > 1 {
						stats = append(stats, SummaryStats{
							Label: fmt.Sprintf("Average %s", strings.Title(strings.ToLower(colName))),
							Value: fmt.Sprintf("%.2f", sum/float64(validCount)),
						})
					}
				}
				break // Only calculate for first numeric column
			}
		}
	}

	return stats
}

// Export CSV
func exportCSV(w http.ResponseWriter, result ReportResult, reportTitle string) {
	w.Header().Set("Content-Type", "text/csv")
	w.Header().Set("Content-Disposition", fmt.Sprintf("attachment; filename=\"%s_%s.csv\"", 
		strings.ReplaceAll(strings.ToLower(reportTitle), " ", "_"),
		time.Now().Format("2006-01-02")))

	// Write header
	fmt.Fprintf(w, "%s\n", strings.Join(result.Columns, ","))

	// Write data
	for _, row := range result.Rows {
		var csvRow []string
		for _, cell := range row {
			// Escape CSV values
			cellStr := fmt.Sprintf("%v", cell)
			if strings.Contains(cellStr, ",") || strings.Contains(cellStr, "\"") || strings.Contains(cellStr, "\n") {
				cellStr = `"` + strings.ReplaceAll(cellStr, `"`, `""`) + `"`
			}
			csvRow = append(csvRow, cellStr)
		}
		fmt.Fprintf(w, "%s\n", strings.Join(csvRow, ","))
	}
}