import Foundation
import UIKit
// MARK: - Memory Leak Prevention
class ImageDownloader {
private var tasks: [URL: URLSessionDataTask] = [:]
func downloadImage(from url: URL, completion: @escaping (UIImage?) -> Void) {
// Cancel existing task if any
tasks[url]?.cancel()
let task = URLSession.shared.dataTask(with: url) { [weak self] data, response, error in
defer { self?.tasks[url] = nil }
guard let data = data, let image = UIImage(data: data) else {
completion(nil)
return
}
completion(image)
}
tasks[url] = task
task.resume()
}
func cancelAll() {
tasks.values.forEach { $0.cancel() }
tasks.removeAll()
}
}
// MARK: - Avoiding Retain Cycles
class PostViewModel {
var onUpdate: (() -> Void)?
private var posts: [Post] = []
func loadPosts() {
// Use [weak self] to avoid retain cycle
URLSession.shared.dataTask(with: URL(string: "https://api.example.com/posts")!) { [weak self] data, _, error in
guard let self = self, let data = data else { return }
if let posts = try? JSONDecoder().decode([Post].self, from: data) {
self.posts = posts
DispatchQueue.main.async { [weak self] in
self?.onUpdate?()
}
}
}.resume()
}
}
// MARK: - Efficient Collection Handling
class DataProcessor {
// Bad: Creating new array each time
func processItemsInefficiently(_ items: [String]) -> [String] {
var result: [String] = []
for item in items {
result.append(item.uppercased())
}
return result
}
// Good: Using functional approach
func processItemsEfficiently(_ items: [String]) -> [String] {
items.map { $0.uppercased() }
}
// Good: Pre-allocating capacity
func processItemsWithCapacity(_ items: [String]) -> [String] {
var result = [String]()
result.reserveCapacity(items.count)
for item in items {
result.append(item.uppercased())
}
return result
}
}
// MARK: - Image Caching for Performance
class PerformantImageCache {
private let cache = NSCache<NSString, UIImage>()
private let fileManager = FileManager.default
private let cacheDirectory: URL
init() {
let paths = fileManager.urls(for: .cachesDirectory, in: .userDomainMask)
cacheDirectory = paths[0].appendingPathComponent("ImageCache")
try? fileManager.createDirectory(at: cacheDirectory, withIntermediateDirectories: true)
// Set memory cache limits
cache.countLimit = 100
cache.totalCostLimit = 50 * 1024 * 1024 // 50 MB
}
func image(forKey key: String) -> UIImage? {
// Check memory cache first
if let cached = cache.object(forKey: key as NSString) {
return cached
}
// Check disk cache
let url = cacheDirectory.appendingPathComponent(key)
if let data = try? Data(contentsOf: url),
let image = UIImage(data: data) {
cache.setObject(image, forKey: key as NSString)
return image
}
return nil
}
func setImage(_ image: UIImage, forKey key: String) {
// Save to memory cache
cache.setObject(image, forKey: key as NSString)
// Save to disk cache asynchronously
DispatchQueue.global(qos: .background).async {
if let data = image.jpegData(compressionQuality: 0.8) {
let url = self.cacheDirectory.appendingPathComponent(key)
try? data.write(to: url)
}
}
}
func clearCache() {
cache.removeAllObjects()
try? fileManager.removeItem(at: cacheDirectory)
try? fileManager.createDirectory(at: cacheDirectory, withIntermediateDirectories: true)
}
}
// MARK: - Performance Monitoring
class PerformanceMonitor {
static func measure(_ label: String, block: () -> Void) {
let start = CFAbsoluteTimeGetCurrent()
block()
let end = CFAbsoluteTimeGetCurrent()
print("\(label) took \(String(format: "%.4f", end - start)) seconds")
}
static func measureAsync(_ label: String, block: () async -> Void) async {
let start = CFAbsoluteTimeGetCurrent()
await block()
let end = CFAbsoluteTimeGetCurrent()
print("\(label) took \(String(format: "%.4f", end - start)) seconds")
}
}
Instruments profiles iOS apps to identify performance bottlenecks, memory leaks, and energy issues. The Time Profiler instrument samples the call stack to show which functions consume CPU time. Allocations tracks memory usage and finds leaks by identifying unreleased objects. Leaks instrument specifically detects retain cycles. I use the SwiftUI View Body instrument to find expensive view updates. Network instrument monitors requests and responses. Energy Log shows battery impact. For debugging, I set strategic breakpoints and use print statements sparingly. The Visual Memory Debugger displays object graphs to spot retain cycles. Running instruments regularly catches regressions before they reach users.