fix: Resolve soft delete and add encrypted config support
- Fix soft delete functionality by filtering out deleted items in search results - Add support for encrypted configuration storage and retrieval - Copy test suite and vitest config to ensure all functionality works - Maintain all core brainy functionality during repository cleanup
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62 changed files with 13792 additions and 6 deletions
234
tests/performance.test.ts
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234
tests/performance.test.ts
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/**
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* Performance Tests
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*
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* Purpose:
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* This test suite measures the performance of Brainy operations with different dataset sizes:
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* 1. Small datasets (10-100 items)
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* 2. Medium datasets (100-1000 items)
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* 3. Large datasets (1000+ items)
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*
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* These tests help identify performance bottlenecks and ensure the library
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* remains efficient as the dataset grows.
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*
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* Note: These tests are marked as "slow" and may take longer to run.
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*/
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import { describe, it, expect, beforeEach, afterEach } from 'vitest'
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import { BrainyData, createStorage } from '../dist/unified.js'
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// Helper function to measure execution time
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const measureExecutionTime = async (fn: () => Promise<any>): Promise<number> => {
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const start = performance.now()
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await fn()
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const end = performance.now()
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return end - start
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}
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// Helper function to generate test data
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const generateTestData = (count: number): string[] => {
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return Array.from({ length: count }, (_, i) => `Test item ${i} with some additional text for embedding`)
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}
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describe('Performance Tests', () => {
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let brainyInstance: any
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beforeEach(async () => {
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// Create a test BrainyData instance with memory storage for faster tests
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const storage = await createStorage({ forceMemoryStorage: true })
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brainyInstance = new BrainyData({
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storageAdapter: storage
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})
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await brainyInstance.init()
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// Clear any existing data to ensure a clean test environment
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await brainyInstance.clear()
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})
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afterEach(async () => {
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// Clean up after each test
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if (brainyInstance) {
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await brainyInstance.clear()
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await brainyInstance.shutDown()
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}
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})
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describe('Small Dataset (10-100 items)', () => {
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it('should add items efficiently', async () => {
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const items = generateTestData(50)
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.addBatch(items)
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})
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console.log(`Adding 50 items took ${executionTime.toFixed(2)}ms (${(executionTime / 50).toFixed(2)}ms per item)`)
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// Verify all items were added
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const size = await brainyInstance.size()
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expect(size).toBe(50)
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// No specific performance assertion, just logging for analysis
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})
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it('should search efficiently', async () => {
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// Add test data
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const items = generateTestData(50)
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await brainyInstance.addBatch(items)
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// Measure search performance
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.search('Test item', 10)
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})
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console.log(`Searching in 50 items took ${executionTime.toFixed(2)}ms`)
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// No specific performance assertion, just logging for analysis
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})
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})
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describe('Medium Dataset (100-1000 items)', () => {
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it('should add items efficiently', async () => {
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const items = generateTestData(200)
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.addBatch(items)
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})
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console.log(`Adding 200 items took ${executionTime.toFixed(2)}ms (${(executionTime / 200).toFixed(2)}ms per item)`)
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// Verify all items were added
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const size = await brainyInstance.size()
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expect(size).toBe(200)
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})
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it('should search efficiently', async () => {
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// Add test data
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const items = generateTestData(200)
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await brainyInstance.addBatch(items)
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// Measure search performance
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.search('Test item', 10)
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})
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console.log(`Searching in 200 items took ${executionTime.toFixed(2)}ms`)
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})
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it('should handle multiple concurrent searches efficiently', async () => {
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// Add test data
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const items = generateTestData(200)
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await brainyInstance.addBatch(items)
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// Perform multiple concurrent searches
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const searchQueries = [
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'Test item 10',
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'Test item 50',
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'Test item 100',
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'Test item 150',
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'Test item 190'
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]
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const executionTime = await measureExecutionTime(async () => {
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await Promise.all(searchQueries.map(query => brainyInstance.search(query, 10)))
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})
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console.log(`5 concurrent searches in 200 items took ${executionTime.toFixed(2)}ms (${(executionTime / 5).toFixed(2)}ms per search)`)
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})
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})
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// Large dataset tests are skipped by default as they can be slow
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// Use .only instead of .skip to run these tests specifically
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describe.skip('Large Dataset (1000+ items)', () => {
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it('should add items efficiently', async () => {
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const items = generateTestData(1000)
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.addBatch(items)
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})
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console.log(`Adding 1000 items took ${executionTime.toFixed(2)}ms (${(executionTime / 1000).toFixed(2)}ms per item)`)
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// Verify all items were added
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const size = await brainyInstance.size()
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expect(size).toBe(1000)
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})
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it('should search efficiently', async () => {
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// Add test data
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const items = generateTestData(1000)
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await brainyInstance.addBatch(items)
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// Measure search performance
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.search('Test item', 10)
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})
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console.log(`Searching in 1000 items took ${executionTime.toFixed(2)}ms`)
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})
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it('should handle multiple concurrent searches efficiently', async () => {
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// Add test data
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const items = generateTestData(1000)
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await brainyInstance.addBatch(items)
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// Perform multiple concurrent searches
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const searchQueries = [
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'Test item 100',
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'Test item 300',
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'Test item 500',
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'Test item 700',
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'Test item 900'
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]
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const executionTime = await measureExecutionTime(async () => {
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await Promise.all(searchQueries.map(query => brainyInstance.search(query, 10)))
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})
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console.log(`5 concurrent searches in 1000 items took ${executionTime.toFixed(2)}ms (${(executionTime / 5).toFixed(2)}ms per search)`)
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})
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})
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describe('Performance Scaling', () => {
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it('should demonstrate search performance scaling with dataset size', async () => {
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// Test with different dataset sizes
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const datasetSizes = [10, 50, 100]
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const results: { size: number; time: number }[] = []
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for (const size of datasetSizes) {
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// Add test data
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const items = generateTestData(size)
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await brainyInstance.addBatch(items)
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// Measure search performance
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const executionTime = await measureExecutionTime(async () => {
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await brainyInstance.search('Test item', 10)
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})
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results.push({ size, time: executionTime })
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// Clear for next iteration
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await brainyInstance.clear()
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}
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// Log results
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console.log('Search Performance Scaling:')
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results.forEach(result => {
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console.log(`Dataset size: ${result.size}, Search time: ${result.time.toFixed(2)}ms`)
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})
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// Calculate scaling factor (how much slower per item)
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if (results.length >= 2) {
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const smallestDataset = results[0]
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const largestDataset = results[results.length - 1]
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const scalingFactor = (largestDataset.time / smallestDataset.time) /
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(largestDataset.size / smallestDataset.size)
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console.log(`Scaling factor: ${scalingFactor.toFixed(2)}x`)
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// Ideally, the scaling factor should be close to 1 (linear scaling)
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// or less than 1 (sub-linear scaling)
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}
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})
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})
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})
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