How to Use is and as Keywords for Type Checking in C#

Slow initial load times can drive users away from your React application. One powerful technique to improve performance is lazy loading - loading components only when they're needed.

Let's explore how to implement this in React.

The Problem with Eager Loading

By default, React bundles all your components together, forcing users to download everything upfront. This makes navigation much quicker and more streamlined once this initial download is complete.

However, depending on the size of your application, it could also create a long initial load time.

import HeavyComponent from './HeavyComponent';
import AnotherHeavyComponent from './AnotherHeavyComponent';

function App() {
  return (
    <div>
      {/* These components load even if user never sees them */}
      <HeavyComponent />
      <AnotherHeavyComponent />
    </div>
  );
}

React.lazy() to the Rescue

React.lazy() lets you defer loading components until they're actually needed:

import React, { lazy, Suspense } from 'react';

// Components are now loaded only when rendered
const HeavyComponent = lazy(() => import('./HeavyComponent'));
const AnotherHeavyComponent = lazy(() => import('./AnotherHeavyComponent'));

function App() {
  return (
    <div>
      <Suspense fallback={<div>Loading...</div>}>
        <HeavyComponent />
        <AnotherHeavyComponent />
      </Suspense>
    </div>
  );
}

Route-Based Lazy Loading

Combine with React Router for even better performance:

import React, { lazy, Suspense } from 'react';
import { BrowserRouter, Routes, Route } from 'react-router-dom';

const Home = lazy(() => import('./pages/Home'));
const Dashboard = lazy(() => import('./pages/Dashboard'));
const Settings = lazy(() => import('./pages/Settings'));

function App() {
  return (
    <BrowserRouter>
      <Suspense fallback={<div>Loading...</div>}>
        <Routes>
          <Route path="/" element={<Home />} />
          <Route path="/dashboard" element={<Dashboard />} />
          <Route path="/settings" element={<Settings />} />
        </Routes>
      </Suspense>
    </BrowserRouter>
  );
}

Implement these techniques in your React application today and watch your load times improve dramatically!

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.

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.