Sreenivasa Reddy Thotli

  Here are some of the top search engines currently: Google : With its powerful algorithms and vast index, Google is undoubtedly the most popular search engine worldwide, handling billions of searches every day. Bing : Microsoft's search engine is the second largest, offering similar features to Google, including web search, image search, and more. Yahoo : While not as dominant as it once was, Yahoo Search still has a significant user base, particularly for news and email services. Baidu : China's leading search engine, Baidu dominates the Chinese market and offers web search, image search, video search, and more. Yandex : Russia's largest search engine, Yandex provides search services as well as a range of other online services, including email and maps. DuckDuckGo : Known for its privacy-focused approach, DuckDuckGo doesn't track users' search history or personalize search results. Ask.com : Once known as Ask Jeeves, Ask.com allows users to ask questions in natura

 Explanation of asynchronous programming in C# using async/await keywords, including best practices and common pitfalls.

 Detailed guide on implementing dependency injection for better code maintainability and testability in ASP.NET Core applications.

 Explore the latest features introduced in C# 9.0, including record types, pattern matching enhancements, and more.

 Explanation of .NET Core's cross-platform capabilities and lightweight nature compared to the traditional .NET Framework.

  Here are some of the top social media websites in India along with their links: Facebook : Facebook remains one of the most visited social media platforms in India, providing a space for users to connect with friends, share updates, and engage with various communities. facebook.com Instagram : Instagram is highly popular in India, particularly among younger users, for sharing photos, videos, and stories. instagram.com WhatsApp : Widely used for messaging, WhatsApp also allows sharing status updates and conducting voice and video calls. whatsapp.com Twitter (now X) : Known for its real-time updates and microblogging capabilities, Twitter is a key platform for news and public discourse in India. twitter.com LinkedIn : This platform is essential for professional networking, job searching, and career development. linkedin.com YouTube : A major platform for video content, YouTube is extensively used for entertainment, education, and marketing. youtube.com Telegram : Popular for its messag

The "best" development technologies can vary depending on the specific requirements of a project, the team's expertise, scalability needs, and other factors. However, here are some widely acclaimed development technologies across various areas of software development: Programming Languages : JavaScript : Widely used for front-end and back-end web development. Python : Known for its simplicity, readability, and vast ecosystem; used in web development, data science, AI, etc. Java : Popular for enterprise-level applications, Android development, and server-side programming. C# : Commonly used for Windows applications, game development (with Unity), and enterprise-level software. Go (Golang) : Known for its efficiency, concurrency support, and simplicity. Swift and Kotlin : For iOS and Android mobile app development respectively. Frameworks and Libraries : React.js, Angular, Vue.js : Front-end frameworks for building dynamic and interactive web applications. Node.js : JavaScr

 Rate limiting can be implemented by tracking the number of API calls made and adding delays if necessary. Here's an example: using System; using System.Net.Http; using System.Text; using System.Threading; using System.Threading.Tasks; using Newtonsoft.Json; namespace ChatGPTExample {     class Program     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         private static int requestCount = 0;         private static readonly int requestLimit = 60; // Example limit         private static readonly TimeSpan timeWindow = TimeSpan.FromMinutes(1);         private static DateTime windowStart = DateTime.UtcNow;         static async Task Main(string[] args)         {             string prompt = "Explain the significance of machine learning in modern technology.";             var response = await GetChatGPTResponseWithRateLimiting(prompt);       

  Here's a step-by-step guide to create a basic chatbot using ChatGPT in a C# WinForms application: Set Up the Project : Create a new C# WinForms App in Visual Studio. Install System.Net.Http and Newtonsoft.Json via NuGet Package Manager. Design the Form : Add a TextBox for user input ( txtUserInput ). Add a Button to send the message ( btnSend ). Add a TextBox for displaying the chat conversation ( txtChat ), set its Multiline property to True . Code Example : using System; using System.Net.Http; using System.Text; using System.Threading.Tasks; using System.Windows.Forms; using Newtonsoft.Json; namespace ChatGPTWinForms {     public partial class Form1 : Form     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         public Form1()         {             InitializeComponent();         }         private async void btnSend_Click(object sender, E

 Error handling can be done using try-catch blocks and checking the HTTP response status. Here's an example: public static async Task<string> GetChatGPTResponse(string prompt) {     using (var httpClient = new HttpClient())     {         httpClient.DefaultRequestHeaders.Add("Authorization", $"Bearer {apiKey}");         var requestBody = new         {             model = "text-davinci-003",             prompt = prompt,             max_tokens = 150         };         var content = new StringContent(JsonConvert.SerializeObject(requestBody), Encoding.UTF8, "application/json");         try         {             var response = await httpClient.PostAsync(endpoint, content);             if (!response.IsSuccessStatusCode)             {                 var errorResponse = await response.Content.ReadAsStringAsync();                 throw new Exception($"API call failed with status code: {response.StatusCode}. Response: {errorResponse}");

  To call OpenAI's ChatGPT API from a C# application, you need to make HTTP requests using HttpClient . Here's an example of how to do this: Set Up the Project : Create a new C# Console Application in Visual Studio. Install System.Net.Http and Newtonsoft.Json via NuGet Package Manager. Sample code  using System; using System.Net.Http; using System.Text; using System.Threading.Tasks; using Newtonsoft.Json; namespace ChatGPTExample {     class Program     {         private static readonly string apiKey = "YOUR_API_KEY_HERE";         private static readonly string endpoint = "https://api.openai.com/v1/completions";         static async Task Main(string[] args)         {             string prompt = "Explain the significance of machine learning in modern technology.";             var response = await GetChatGPTResponse(prompt);             Console.WriteLine(response);         }         public static async Task<string> GetChatGPTResponse(string p

  This example fetches data from a URL asynchronously without blocking the main thread, demonstrating the use of async and await . By providing detailed Q&A like these on your blog, you can offer valuable solutions to your readers, helping them tackle complex SQL and C# challenges effectively. using System; using System.Net.Http; using System.Threading.Tasks; class Program {     static async Task Main(string[] args)     {         string url = "https://api.github.com/repos/dotnet/roslyn";         string result = await FetchDataAsync(url);         Console.WriteLine(result);     }     public static async Task<string> FetchDataAsync(string url)     {         using (HttpClient client = new HttpClient())         {             client.DefaultRequestHeaders.UserAgent.TryParseAdd("request");             HttpResponseMessage response = await client.GetAsync(url);             response.EnsureSuccessStatusCode();             string responseBody = await response.Content.

  Implementing dependency injection in a .NET Core console application involves setting up a ServiceCollection , configuring services, and building a service provider. Example: using Microsoft.Extensions.DependencyInjection; using System; namespace ConsoleAppDI { public interface IGreetingService { void Greet(string name); } public class GreetingService : IGreetingService { public void Greet(string name) { Console.WriteLine($"Hello, {name}!"); } } class Program { static void Main(string[] args) { // Setup DI var serviceCollection = new ServiceCollection(); ConfigureServices(serviceCollection); var serviceProvider = serviceCollection.BuildServiceProvider(); // Get service and use it var greeter = serviceProvider.GetService<IGreetingService>(); greeter.Greet("World"); } pri

  Deadlocks occur when two or more sessions permanently block each other. To handle and prevent deadlocks: Identify Deadlocks : Use the SQL Server error log or Extended Events to capture deadlock information. Enable trace flags 1204 and 1222 for detailed deadlock information. Deadlock Prevention : Ensure consistent access order for resources in your transactions. Keep transactions short and minimize lock duration. Use lower isolation levels if appropriate (e.g., READ COMMITTED instead of SERIALIZABLE ). Retry Logic : Implement retry logic in your application to handle deadlock exceptions gracefully. Use TRY...CATCH in T-SQL to handle deadlock errors.

  Optimizing a slow-running query involves several steps: Identify the Bottleneck : Use SQL Server Profiler or Extended Events to identify slow queries. Use Execution Plans to understand how SQL Server processes your query. Index Optimization : Ensure proper indexing on columns used in WHERE , JOIN , and ORDER BY clauses. Avoid over-indexing, which can slow down INSERT and UPDATE operations. Query Rewriting : Simplify complex queries and break them into smaller parts if necessary. Avoid SELECT * and only fetch necessary columns. Use EXISTS instead of IN for subqueries. Statistics Update : Regularly update statistics using UPDATE STATISTICS to ensure the query optimizer has accurate data. Temp Tables and Table Variables : Use temporary tables or table variables wisely. Temp tables can be indexed, which may improve performance in some cases. Use of Proper Joins : Prefer INNER JOIN over LEFT JOIN if you only need matching records.