How to Read a File Line by Line in C#?

When working with URLs in C#, encoding is essential to ensure that special characters (like spaces, ?, &, and =) don’t break the URL structure. The recommended way to encode a string for a URL is by using Uri.EscapeDataString(), which converts unsafe characters into their percent-encoded equivalents.

string rawText = "hello world!";
string encodedText = Uri.EscapeDataString(rawText);

Console.WriteLine(encodedText); // Output: hello%20world%21

This method encodes spaces as %20, making it ideal for query parameters.

For ASP.NET applications, you can also use HttpUtility.UrlEncode() (from System.Web), which encodes spaces as +:

using System.Web;

string encodedText = HttpUtility.UrlEncode("hello world!");
Console.WriteLine(encodedText); // Output: hello+world%21

For .NET Core and later, Uri.EscapeDataString() is the preferred choice.

Using SqlDataReader asynchronously prevents blocking the main thread, improving performance in web apps and large queries. Here’s how to do it properly.

Use await with ExecuteReaderAsync()

using (SqlConnection conn = new SqlConnection(connectionString))
{
    await conn.OpenAsync();
    using (SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn))
    using (SqlDataReader reader = await cmd.ExecuteReaderAsync()) 
    {
        while (await reader.ReadAsync()) 
        {
            Console.WriteLine(reader["Username"]);
        }
    } // ✅ Auto-closes reader
} // ✅ Auto-closes connection

Why use async?

A couple of reasons:

• Frees up the thread while waiting for the database.
• Improves scalability in ASP.NET Core and web apps.

⚡ Alternative: ConfigureAwait(false) for ASP.NET

Use ConfigureAwait(false) in library code to avoid deadlocks in UI frameworks like ASP.NET.

using (SqlConnection conn = new SqlConnection(connectionString))
{
    await conn.OpenAsync().ConfigureAwait(false);
    using (SqlCommand cmd = new SqlCommand("SELECT * FROM Users", conn))
    using (SqlDataReader reader = await cmd.ExecuteReaderAsync().ConfigureAwait(false)) 
    {
        while (await reader.ReadAsync().ConfigureAwait(false)) 
        {
            Console.WriteLine(reader["Username"]);
        }
    }
}

Removing duplicates from a list in C# is a common task, especially when working with large datasets. C# provides multiple ways to achieve this efficiently, leveraging built-in collections and LINQ.

Using HashSet (Fastest for Unique Elements)

A HashSet<T> automatically removes duplicates since it only stores unique values. This is one of the fastest methods:

List<int> numbers = new List<int> { 1, 2, 2, 3, 4, 4, 5 };
numbers = new HashSet<int>(numbers).ToList();
Console.WriteLine(string.Join(", ", numbers)); // Output: 1, 2, 3, 4, 5

Using LINQ Distinct (Concise and Readable)

LINQ’s Distinct() method provides an elegant way to remove duplicates:

List<int> numbers = new List<int> { 1, 2, 2, 3, 4, 4, 5 };
numbers = numbers.Distinct().ToList();
Console.WriteLine(string.Join(", ", numbers)); // Output: 1, 2, 3, 4, 5

Removing Duplicates by Custom Property (For Complex Objects)

When working with objects, DistinctBy() from .NET 6+ simplifies duplicate removal based on a property:

using System.Linq;
using System.Collections.Generic;

class Person
{
    public string Name { get; set; }
    public int Age { get; set; }
}

List<Person> people = new List<Person>
{
    new Person { Name = "Alice", Age = 30 },
    new Person { Name = "Bob", Age = 25 },
    new Person { Name = "Alice", Age = 30 }
};

people = people.DistinctBy(p => p.Name).ToList();
Console.WriteLine(string.Join(", ", people.Select(p => p.Name))); // Output: Alice, Bob

For earlier .NET versions, use GroupBy():

people = people.GroupBy(p => p.Name).Select(g => g.First()).ToList();

Performance Considerations

• HashSet<T> is the fastest but only works for simple types.
• Distinct() is easy to use but slower than HashSet<T> for large lists.
• DistinctBy() (or GroupBy()) is useful for complex objects but may have performance trade-offs.

Conclusion

Choosing the best approach depends on the data type and use case. HashSet<T> is ideal for primitive types, Distinct() is simple and readable, and DistinctBy() (or GroupBy()) is effective for objects.