Mastering C# Collections: IEnumerable vs ICollection vs IList for Clean, Efficient Code
C# Collections: IEnumerable vs ICollection vs IList
When working with collections in C#, understanding the distinctions between IEnumerable<T>, ICollection<T>, and IList<T> is essential for writing scalable, maintainable, and performant applications.
1️⃣ IEnumerable<T>: Best for Iteration & Querying
Ideal Use Cases:
- Lazy evaluation for handling large datasets efficiently.
- Read-only access without modifying the collection.
- Supports LINQ queries for filtering and transformation.
Example:
using System.Collections.Generic;
IEnumerable<int> numbers = new List<int> { 1, 2, 3, 4, 5 };
foreach (var number in numbers)
{
Console.WriteLine(number); // Iterating forward only
}
2️⃣ ICollection<T>: Supports Modification & Sizing
Ideal Use Cases:
- Adding, removing, and clearing elements.
- Maintaining a
Countproperty for efficient sizing. - General data management operations within collections.
Example:
using System.Collections.Generic;
ICollection<int> numbers = new List<int> { 1, 2, 3 };
numbers.Add(4); // Allowed in ICollection
numbers.Remove(2);
Console.WriteLine(numbers.Count); // Output: 3
3️⃣ IList<T>: Ordered & Index-Based Data Management
Ideal Use Cases:
- Maintaining order within collections.
- Direct index access and manipulation (
numbers[0]). - Managing lists used in UI, task management, and queues.
Example:
using System.Collections.Generic;
IList<string> names = new List<string> { "Alice", "Bob", "Charlie" };
names[1] = "David"; // Modify element at index 1
Console.WriteLine(names[1]); // Output: David
🚀 Why Choosing the Right Interface Matters
Understanding when to use IEnumerable, ICollection, or IList ensures:
- ✔ Optimized performance by avoiding unnecessary operations.
- ✔ Cleaner code that follows best practices.
- ✔ Scalability for large datasets and evolving applications.
Which collection interface do you use most—and why? Drop your thoughts in the comments below! 👇
#CSharp #DotNetCore #CleanCode #SoftwareEngineering #PerformanceOptimization #BackendDevelopment #CodingBestPractices

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