@simonecoelhosfo/optimizely-mcp-server/dist/cli/progress-reporters/SummaryReporter.js

Optimizely MCP Server for AI assistants with integrated CLI tools

/**
 * Summary Report Generator for Performance Optimization
 * @description Generates comprehensive performance reports with detailed metrics,
 * SQL operation analysis, and optimization recommendations based on sync results.
 *
 * Features:
 * - Performance metrics visualization
 * - SQL operation reduction analysis
 * - Entity-specific performance breakdowns
 * - Time complexity analysis
 * - Optimization recommendations
 * - Export to various formats (console, JSON, markdown)
 *
 * @author Optimizely MCP Server
 * @version 2.0.0
 */
import chalk from 'chalk';
import { writeFileSync } from 'fs';
/**
 * Summary Report Generator
 */
export class SummaryReporter {
    report;
    constructor() {
        this.report = this.initializeReport();
    }
    /**
     * Initialize empty report structure
     */
    initializeReport() {
        return {
            summary: {
                totalDuration: 0,
                totalEntities: 0,
                totalRecords: 0,
                totalSqlBefore: 0,
                totalSqlAfter: 0,
                overallReduction: 0,
                achievedTarget: false
            },
            entityMetrics: [],
            phaseTimings: {},
            recommendations: [],
            timestamp: new Date().toISOString(),
            configuration: {
                batchSize: 100,
                platform: 'Feature & Web Experimentation',
                projectCount: 0
            }
        };
    }
    /**
     * Add entity performance metrics
     */
    addEntityMetrics(metrics) {
        this.report.entityMetrics.push(metrics);
        // Update summary
        this.report.summary.totalEntities++;
        this.report.summary.totalRecords += metrics.recordCount;
        this.report.summary.totalSqlBefore += metrics.sqlOperationsBefore;
        this.report.summary.totalSqlAfter += metrics.sqlOperationsAfter;
    }
    /**
     * Add phase timing
     */
    addPhaseTiming(phase, duration) {
        this.report.phaseTimings[phase] = duration;
    }
    /**
     * Calculate final metrics and generate recommendations
     */
    finalize(totalDuration, projectCount) {
        this.report.summary.totalDuration = totalDuration;
        this.report.configuration.projectCount = projectCount;
        // Calculate overall reduction
        if (this.report.summary.totalSqlBefore > 0) {
            this.report.summary.overallReduction =
                ((this.report.summary.totalSqlBefore - this.report.summary.totalSqlAfter) /
                    this.report.summary.totalSqlBefore) * 100;
            this.report.summary.achievedTarget = this.report.summary.overallReduction >= 90;
        }
        // Generate recommendations
        this.generateRecommendations();
    }
    /**
     * Generate optimization recommendations based on metrics
     */
    generateRecommendations() {
        const { summary, entityMetrics } = this.report;
        // Achievement recognition
        if (summary.achievedTarget) {
            this.report.recommendations.push('🎯 Excellent! Achieved target of 90%+ SQL operation reduction.');
        }
        else {
            this.report.recommendations.push(`⚠️ SQL reduction of ${summary.overallReduction.toFixed(1)}% is below 90% target.`);
        }
        // Find slowest entities
        const slowestEntity = entityMetrics.reduce((prev, curr) => curr.syncDuration > prev.syncDuration ? curr : prev, entityMetrics[0]);
        if (slowestEntity && slowestEntity.syncDuration > 5000) {
            this.report.recommendations.push(`🐌 ${slowestEntity.entityType} sync took ${(slowestEntity.syncDuration / 1000).toFixed(1)}s. Consider optimizing API pagination.`);
        }
        // Large dataset recommendations
        const largeEntities = entityMetrics.filter(e => e.recordCount > 100);
        if (largeEntities.length > 0) {
            this.report.recommendations.push(`📊 Large datasets detected (${largeEntities.map(e => e.entityType).join(', ')}). Consider increasing batch size for better performance.`);
        }
        // Low reduction entities
        const lowReductionEntities = entityMetrics.filter(e => e.reductionPercent < 90);
        if (lowReductionEntities.length > 0) {
            this.report.recommendations.push(`⚡ Entities with sub-optimal reduction: ${lowReductionEntities.map(e => `${e.entityType} (${e.reductionPercent.toFixed(1)}%)`).join(', ')}`);
        }
        // General recommendations
        if (summary.totalDuration > 60000) {
            this.report.recommendations.push('⏱️ Consider implementing parallel project sync for multi-project scenarios.');
        }
        if (this.report.configuration.projectCount > 5) {
            this.report.recommendations.push('🔄 With multiple projects, incremental sync can significantly reduce sync time.');
        }
    }
    /**
     * Generate console output
     */
    toConsole() {
        const { summary, entityMetrics, phaseTimings, recommendations } = this.report;
        console.log('\n' + chalk.bold.blue('═'.repeat(80)));
        console.log(chalk.bold.white.bgBlue(' PERFORMANCE OPTIMIZATION SUMMARY REPORT '));
        console.log(chalk.blue('═'.repeat(80)));
        // Summary Section
        console.log(chalk.bold('\n📊 OVERALL PERFORMANCE:'));
        console.log(chalk.white(`  Total Duration: ${(summary.totalDuration / 1000).toFixed(2)}s`));
        console.log(chalk.white(`  Total Entities: ${summary.totalEntities}`));
        console.log(chalk.white(`  Total Records: ${summary.totalRecords.toLocaleString()}`));
        console.log(chalk.bold.green(`  SQL Operations: ${summary.totalSqlBefore.toLocaleString()} → ${summary.totalSqlAfter.toLocaleString()}`));
        console.log(chalk.bold.green(`  Reduction: ${summary.overallReduction.toFixed(1)}%`));
        if (summary.achievedTarget) {
            console.log(chalk.bold.green(`  🎯 TARGET ACHIEVED! (90%+ reduction)`));
        }
        // Entity Breakdown
        console.log(chalk.bold('\n📦 ENTITY PERFORMANCE BREAKDOWN:'));
        console.log(chalk.gray('─'.repeat(80)));
        console.log(chalk.bold('Entity Type'.padEnd(20) +
            'Records'.padEnd(10) +
            'SQL Before'.padEnd(12) +
            'SQL After'.padEnd(12) +
            'Reduction'.padEnd(12) +
            'Time'.padEnd(10) +
            'Avg/Record'));
        console.log(chalk.gray('─'.repeat(80)));
        entityMetrics
            .sort((a, b) => b.recordCount - a.recordCount)
            .forEach(metric => {
            const reductionColor = metric.reductionPercent >= 90 ? chalk.green : chalk.yellow;
            console.log(metric.entityType.padEnd(20) +
                metric.recordCount.toString().padEnd(10) +
                metric.sqlOperationsBefore.toString().padEnd(12) +
                metric.sqlOperationsAfter.toString().padEnd(12) +
                reductionColor(`${metric.reductionPercent.toFixed(1)}%`.padEnd(12)) +
                `${(metric.syncDuration / 1000).toFixed(2)}s`.padEnd(10) +
                `${metric.averageTimePerRecord.toFixed(0)}ms`);
        });
        console.log(chalk.gray('─'.repeat(80)));
        // Phase Timings
        console.log(chalk.bold('\n⏱️  PHASE TIMINGS:'));
        Object.entries(phaseTimings)
            .sort(([, a], [, b]) => b - a)
            .forEach(([phase, duration]) => {
            const percentage = (duration / summary.totalDuration * 100).toFixed(1);
            const bar = '█'.repeat(Math.floor(parseInt(percentage) / 2));
            console.log(chalk.white(`  ${phase.padEnd(30)} ${bar} ${(duration / 1000).toFixed(2)}s (${percentage}%)`));
        });
        // Recommendations
        if (recommendations.length > 0) {
            console.log(chalk.bold('\n💡 RECOMMENDATIONS:'));
            recommendations.forEach(rec => {
                console.log(chalk.yellow(`  ${rec}`));
            });
        }
        // Configuration
        console.log(chalk.bold('\n⚙️  CONFIGURATION:'));
        console.log(chalk.gray(`  Batch Size: ${this.report.configuration.batchSize}`));
        console.log(chalk.gray(`  Platform: ${this.report.configuration.platform}`));
        console.log(chalk.gray(`  Projects: ${this.report.configuration.projectCount}`));
        console.log(chalk.gray(`  Generated: ${new Date(this.report.timestamp).toLocaleString()}`));
        console.log('\n' + chalk.blue('═'.repeat(80)) + '\n');
    }
    /**
     * Export to JSON file
     */
    toJSON(filepath) {
        const json = JSON.stringify(this.report, null, 2);
        if (filepath) {
            writeFileSync(filepath, json, 'utf-8');
            console.log(chalk.green(`✓ Report saved to: ${filepath}`));
        }
        return json;
    }
    /**
     * Export to Markdown format
     */
    toMarkdown(filepath) {
        const { summary, entityMetrics, phaseTimings, recommendations } = this.report;
        let markdown = `# Performance Optimization Summary Report

Generated: ${new Date(this.report.timestamp).toLocaleString()}

## 📊 Overall Performance

| Metric | Value |
|--------|-------|
| **Total Duration** | ${(summary.totalDuration / 1000).toFixed(2)}s |
| **Total Entities** | ${summary.totalEntities} |
| **Total Records** | ${summary.totalRecords.toLocaleString()} |
| **SQL Operations** | ${summary.totalSqlBefore.toLocaleString()} → ${summary.totalSqlAfter.toLocaleString()} |
| **Reduction** | ${summary.overallReduction.toFixed(1)}% |
| **Target Achieved** | ${summary.achievedTarget ? '✅ Yes (90%+)' : '❌ No'} |

## 📦 Entity Performance Breakdown

| Entity Type | Records | SQL Before | SQL After | Reduction | Sync Time | Avg/Record |
|-------------|---------|------------|-----------|-----------|-----------|------------|
`;
        entityMetrics
            .sort((a, b) => b.recordCount - a.recordCount)
            .forEach(metric => {
            markdown += `| ${metric.entityType} | ${metric.recordCount} | ${metric.sqlOperationsBefore} | ${metric.sqlOperationsAfter} | ${metric.reductionPercent.toFixed(1)}% | ${(metric.syncDuration / 1000).toFixed(2)}s | ${metric.averageTimePerRecord.toFixed(0)}ms |\n`;
        });
        markdown += `
## ⏱️ Phase Timings

| Phase | Duration | Percentage |
|-------|----------|------------|
`;
        Object.entries(phaseTimings)
            .sort(([, a], [, b]) => b - a)
            .forEach(([phase, duration]) => {
            const percentage = (duration / summary.totalDuration * 100).toFixed(1);
            markdown += `| ${phase} | ${(duration / 1000).toFixed(2)}s | ${percentage}% |\n`;
        });
        if (recommendations.length > 0) {
            markdown += `
## 💡 Recommendations

`;
            recommendations.forEach(rec => {
                markdown += `- ${rec}\n`;
            });
        }
        markdown += `
## ⚙️ Configuration

- **Batch Size**: ${this.report.configuration.batchSize}
- **Platform**: ${this.report.configuration.platform}
- **Projects**: ${this.report.configuration.projectCount}
`;
        if (filepath) {
            writeFileSync(filepath, markdown, 'utf-8');
            console.log(chalk.green(`✓ Markdown report saved to: ${filepath}`));
        }
        return markdown;
    }
    /**
     * Get raw report data
     */
    getReport() {
        return this.report;
    }
    /**
     * Create entity metrics from progress data
     */
    static createEntityMetrics(entityType, recordCount, syncDuration, batchOperations = 1) {
        const sqlOperationsBefore = recordCount; // Individual inserts
        const sqlOperationsAfter = batchOperations; // Batch inserts
        const reductionPercent = ((sqlOperationsBefore - sqlOperationsAfter) / sqlOperationsBefore) * 100;
        const averageTimePerRecord = recordCount > 0 ? syncDuration / recordCount : 0;
        return {
            entityType,
            recordCount,
            sqlOperationsBefore,
            sqlOperationsAfter,
            reductionPercent,
            syncDuration,
            averageTimePerRecord,
            batchSize: Math.ceil(recordCount / batchOperations)
        };
    }
}
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