String Interpolation in C#: A Cleaner Way to Format Strings

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.

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!

Understanding the difference between COUNT() and COUNT(DISTINCT) in SQL is crucial for accurate data analysis.

COUNT() returns the total number of rows that match your query criteria, including duplicates, while COUNT(DISTINCT) returns the number of unique values in a specified column, effectively eliminating duplicates from the count.

For example, if you have a table of customer orders where a single customer can place multiple orders, COUNT(customer_id) would give you the total number of orders, whereas COUNT(DISTINCT customer_id) would tell you how many unique customers have placed orders.

The choice between these functions depends on your specific reporting needs. Use COUNT() when you need the total number of records, such as counting all sales transactions or total number of website visits.

Use COUNT(DISTINCT) when you need to know unique occurrences, like the number of different products sold or unique visitors to your website. It's also worth noting that COUNT(*) counts all rows including NULL values, while COUNT(column_name) excludes NULL values from that specific column, which can lead to different results depending on your data structure.

Example

-- Example table: customer_orders
-- customer_id | order_date  | product_id
-- 1          | 2024-01-01  | 100
-- 1          | 2024-01-02  | 101
-- 2          | 2024-01-01  | 100
-- 3          | 2024-01-03  | 102

-- Count all orders
SELECT COUNT(*) as total_orders
FROM customer_orders;
-- Result: 4 (counts all rows)

-- Count unique customers who placed orders
SELECT COUNT(DISTINCT customer_id) as unique_customers
FROM customer_orders;
-- Result: 3 (counts unique customer_ids: 1, 2, 3)

-- Count unique products ordered
SELECT COUNT(DISTINCT product_id) as unique_products
FROM customer_orders;
-- Result: 3 (counts unique product_ids: 100, 101, 102)

-- Compare regular COUNT with COUNT DISTINCT
SELECT 
    COUNT(customer_id) as total_orders,
    COUNT(DISTINCT customer_id) as unique_customers
FROM customer_orders;
-- Result: total_orders = 4, unique_customers = 3