Lazy collections for performance
📖 Scenario: Imagine you have a long list of numbers representing daily sales in a store. You want to find all sales that are bigger than 50 but you want to do it efficiently without checking every number immediately.
🎯 Goal: You will create a list of sales, then use a lazy collection to filter sales greater than 50. Finally, you will print the filtered sales. This shows how lazy collections help improve performance by delaying work until needed.
📋 What You'll Learn
Create an array called
sales with these exact values: [10, 55, 30, 75, 20, 90]Create a lazy collection called
lazySales from the sales arrayUse
lazySales to filter sales greater than 50 and store in filteredSalesPrint
filteredSales converted to an array💡 Why This Matters
🌍 Real World
Lazy collections are useful when working with large data sets where you want to avoid doing all the work upfront. For example, filtering or transforming big lists of sales, logs, or sensor data only when needed.
💼 Career
Understanding lazy collections helps you write efficient Swift code that performs better in apps, especially when handling large or complex data. This skill is valuable for iOS developers and software engineers working on performance-critical applications.
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