Using C# Record Types for Immutable Data Models

Primary constructors, introduced in C# 12, offer a more concise way to define class parameters and initialize fields.

This feature reduces boilerplate code and makes classes more readable.

Traditional Approach vs Primary Constructor

Before primary constructors, you would likely write something like the following:

public class UserService
{
    private readonly ILogger _logger;
    private readonly IUserRepository _repository;

    public UserService(ILogger logger, IUserRepository repository)
    {
        _logger = logger;
        _repository = repository;
    }

    public async Task<User> GetUserById(int id)
    {
        _logger.LogInformation("Fetching user {Id}", id);
        return await _repository.GetByIdAsync(id);
    }
}

With primary constructors, this becomes:

public class UserService(ILogger logger, IUserRepository repository)
{
    public async Task<User> GetUserById(int id)
    {
        logger.LogInformation("Fetching user {Id}", id);
        return await repository.GetByIdAsync(id);
    }
}

Key Benefits

1. Reduced Boilerplate: No need to declare private fields and write constructor assignments
2. Parameters Available Throughout: Constructor parameters are accessible in all instance methods
3. Immutability by Default: Parameters are effectively readonly without explicit declaration

Real-World Example

Here's a practical example using primary constructors with dependency injection:

public class OrderProcessor(
    IOrderRepository orderRepo,
    IPaymentService paymentService,
    ILogger<OrderProcessor> logger)
{
    public async Task<OrderResult> ProcessOrder(Order order)
    {
        try
        {
            logger.LogInformation("Processing order {OrderId}", order.Id);
            
            var paymentResult = await paymentService.ProcessPayment(order.Payment);
            if (!paymentResult.Success)
            {
                return new OrderResult(false, "Payment failed");
            }

            await orderRepo.SaveOrder(order);
            return new OrderResult(true, "Order processed successfully");
        }
        catch (Exception ex)
        {
            logger.LogError(ex, "Failed to process order {OrderId}", order.Id);
            throw;
        }
    }
}

Tips and Best Practices

1. Use primary constructors when the class primarily needs dependencies for its methods
2. Combine with records for immutable data types:

public record Customer(string Name, string Email)
{
    public string FormattedEmail => $"{Name} <{Email}>";
}

3. Consider traditional constructors for complex initialization logic

Primary constructors provide a cleaner, more maintainable way to write C# classes, especially when working with dependency injection and simple data objects.

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 SQL Server, you may often need to count the number of unique values in a specific column. This is useful for analyzing data, detecting duplicates, and understanding dataset distributions.

Using COUNT(DISTINCT column_name)

To count the number of unique values in a column, SQL Server provides the COUNT(DISTINCT column_name) function. Here’s a simple example:

SELECT COUNT(DISTINCT column_name) AS distinct_count
FROM table_name;

This query will return the number of unique values in column_name.

Counting Distinct Values Across Multiple Columns

If you need to count distinct combinations of multiple columns, you can use a subquery:

SELECT COUNT(*) AS distinct_count
FROM (SELECT DISTINCT column1, column2 FROM table_name) AS subquery;

This approach ensures that only unique pairs of column1 and column2 are counted.

Why Use COUNT DISTINCT?

• Helps in identifying unique entries in a dataset.
• Useful for reporting and analytics.
• Efficient way to check for duplicates.

By leveraging COUNT(DISTINCT column_name), you can efficiently analyze your database and extract meaningful insights. Happy querying!