API vs REST API — Quick Quiz for Developers Let’s test your knowledge: 1️⃣ What does API stand for? A) Application Programming Interface B) Advanced Program Internet 2️⃣ REST API uses which protocol? A) HTTP B) FTP 3️⃣ REST API usually uses which data format? A) JSON B) XML 4️⃣ Is every REST API an API? A) Yes B) No 5️⃣ Is every API a REST API? A) Yes B) No Comment your answers below 👇 #API #RESTAPI #WebDevelopment #Programming #Developers #Coding #SoftwareDevelopment #Tech #Backend #LinkedInDevelopers
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API vs REST API — Quiz Time 1. API stands for? A) Application Programming Interface B) Advanced Program Internet 2. REST API uses? A) HTTP B) FTP 3. REST API uses? A) JSON B) XML 4. Every REST API is an API? A) Yes B) No 5. Every API is REST API? A) Yes B) No Comment your answers and check your knowledge. #API #RESTAPI #Programming #WebDevelopment #Coding #Developer #Tech #Backend #LearningToCode
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🚨 90% of developers use HTTP methods incorrectly… If you work on APIs or backend, these basics MUST be clear 👇 GET = fetch data POST = create data PUT = full update PATCH = partial update DELETE = remove data ⚡ Sounds simple… but these mistakes are what create bugs. 💬 Comment “API” if this is clear 🔔 Follow @DevelopersStreet for daily dev content 🌐 www.developersstreet.com 📞 +91 94128 92908 #HTTP #API #RESTAPI #WebDevelopment #Coding #Programming #DeveloperLife #BackendDeveloper #FrontendDeveloper #FullStackDeveloper #LearnToCode #CodingTips #DevTips #SoftwareDevelopment #TechCommunity #LinkedInLearning
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One thing production teaches you quickly: Logs are more valuable than code. When everything works, code matters. When something breaks at 2 AM… Logs matter more. In real systems, issues rarely reproduce locally. Instead you rely on logs to answer questions like: • What exactly happened? • Which service failed? • What request triggered it? • What was the state before the error? Good logging turns chaos into clarity. Some simple practices that make a huge difference: 🔹 Log meaningful events, not just errors 🔹 Include request IDs for traceability 🔹 Avoid logging sensitive data 🔹 Keep logs structured and searchable 🔹 Log context, not just messages Bad logs say: “Something went wrong.” Good logs say: “PaymentService failed for OrderID=10482 due to timeout after 3 retries.” Observability is not a luxury anymore. It’s survival for modern distributed systems. Because when systems grow… Debugging without good logs becomes almost impossible. What’s the most useful log message you’ve ever seen in production? #softwareengineering #java #backend #microservices #devops #observability #systemdesign #developers #programming
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Debugging be like… Nothing works… until it suddenly does. Code breaks → “Must be logic issue” Check logic → “Looks fine” Check API → “Response correct” Restart server → “Still broken” Change nothing → “Now it works” At some point, you accept: You didn’t fix the bug. The bug fixed itself. So I follow one rule now: - Take a break - Come back fresh - Question everything again Because debugging is not coding. It’s detective work. What’s the weirdest bug you ever fixed? 👇 #debugging #developers #codinglife #programming #devlife #Laravel #BackendDevelopment #WebDevelopment #SoftwareEngineering #CodingLife #Developers #API #Tech #Programming #BuildInPublic
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🚀 How C# Code Becomes Machine Language (In Simple Terms) Ever wondered what really happens when you hit Run in C#? It’s not magic—it’s a beautifully engineered pipeline 👇 💡 Step-by-Step Flow (Simplified) 1️⃣ You write C# code Example: #Sample_Code Console.WriteLine("Hello World"); 2️⃣ Compilation (csc.exe) 👉 Your code is converted into Intermediate Language (IL) — not machine code yet Think of IL as a universal language understood by .NET 3️⃣ Assembly Creation (.exe / .dll) 👉 IL + Metadata (info about types, methods, references) = Assembly 4️⃣ CLR (Common Language Runtime) kicks in 👉 Acts like a smart manager ✔ Memory management (GC) ✔ Security checks ✔ Exception handling 5️⃣ JIT Compiler (Just-In-Time) 👉 Converts IL → Native Machine Code (only when needed) Example: * First time method runs → compiled * Next time → reused (fast ⚡) 6️⃣ CPU Executes 👉 Finally, your code runs as machine instructions (0s & 1s) 🎯 Real-Life Analogy 🧑🍳 C# Code = Recipe 📄 IL Code = Universal Recipe Format 👨🍳 JIT = Chef cooking fresh dish 🔥 Machine Code = Ready-to-eat food 💥 Why This Model is Powerful ✔ Platform Independence → Same IL runs anywhere with CLR ✔ Performance → JIT optimizes at runtime ✔ Security → Code verification before execution ✔ Memory Efficiency → Garbage Collector handles cleanup 🔥 Pro Tip (Used by Architects) Use ReadyToRun / AOT when startup performance matters (e.g., microservices) Use JIT when runtime optimization is more important 📌 Key Takeaway C# doesn’t directly compile to machine code 👉 It uses a 2-step smart execution model (IL + JIT) And that’s what makes .NET both flexible + powerful 💬 What’s your take—JIT or AOT for modern apps? #dotnet #csharp #softwarearchitecture #backend #programming #developers #learning #tech #coding #systemdesign
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One thing I learned as a developer: Understanding the problem is harder than writing the code. Recently I had a situation: Everything looked correct, but the system behaved unpredictably. Instead of rewriting code, I: - checked logs - reproduced the issue step by step - analyzed data flow Turned out the issue was in configuration, not logic. Lesson: - Don’t rush into coding - Debug first, code later #programming #debugging #backend #developers
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🚀 Unleash the power of APIs with this comprehensive guide! 🌟 Ever wondered how apps communicate with each other? APIs are like messengers that allow different software applications to talk to each other. As a developer, understanding APIs is crucial for building seamless integrations, accessing external services, and improving your app's functionality. Let's break it down step by step: 1️⃣ First, initialize the API connection 2️⃣ Next, send a request to the API endpoint 3️⃣ Then, receive and handle the response data Check out this code snippet for a basic API call in Python: ```python import requests url = 'https://lnkd.in/gc8PxW6P' response = requests.get(url) data = response.json() print(data) ``` Pro Tip: Always review the API documentation to understand available endpoints and request parameters better. 📚 Common Mistake Alert: Forgetting to handle errors in the API response can lead to unexpected behavior in your application. Always implement error-handling mechanisms for a robust solution. 🛠 🤔 What's your favorite API integration experience as a developer? Share below! 👇 🌐 View my full portfolio and more dev resources at tharindunipun.lk #API #Integration #Developers #CodeSnippet #Programming #TechTalk #ProTip #ErrorHandling #FeedbackWelcome
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I focus on building backend systems that don’t just work they scale. Most of my time goes into things that aren’t always visible at first: How data flows through the system How different parts communicate How the system behaves under load Anyone can make something work for a few users. What matters is how it behaves when usage grows. That’s where small decisions start to matter: Database queries API structure Handling edge cases Keeping the logic predictable Over time, I’ve found myself naturally thinking more about these things while building. Not trying to over-engineer, but making sure the foundation is solid. Because fixing things later is always more expensive than designing them well early. Still learning, still improving but this is the kind of work I enjoy the most. Curious what part of backend development do you enjoy the most? #softwareengineering #backenddevelopment #systemdesign #scalability #programming #webdevelopment
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Many testers focus on tools, but strong frameworks are built on OOP fundamentals. Inheritance avoids repeating setup and common utilities. Encapsulation keeps locators and actions inside page classes, reducing risk. Abstraction hides implementation and keeps tests easy to read. Polymorphism helps handle different browsers or environments with the same code. Constructors help initialize drivers and test data properly. Interfaces make your framework more flexible and extensible. Collections simplify handling dynamic test data. Framework quality is not about how many tools you use it’s about how well your design holds up. Strong OOP skills turn automation from scripts into structured, scalable systems. <~#𝑷𝒍𝒂𝒚𝒘𝒓𝒊𝒈𝒉𝒕 #𝑻𝒆𝒔𝒕𝒊𝒏𝒈~> 𝑷𝒍𝒂𝒚𝒘𝒓𝒊𝒈𝒉𝒕 𝒘𝒊𝒕𝒉 𝑱𝒂𝒗𝒂𝑺𝒄𝒓𝒊𝒑𝒕& 𝑻𝒚𝒑𝒆𝑺𝒄𝒓𝒊𝒑𝒕 ( 𝑨𝑰 𝒊𝒏 𝑻𝒆𝒔𝒕𝒊𝒏𝒈, 𝑮𝒆𝒏𝑨𝑰, 𝑷𝒓𝒐𝒎𝒑𝒕 𝑬𝒏𝒈𝒊𝒏𝒆𝒆𝒓𝒊𝒏𝒈)—𝑻𝒓𝒂𝒊𝒏𝒊𝒏𝒈 𝑺𝒕𝒂𝒓𝒕𝒔 𝒇𝒓𝒐𝒎 21st 𝑨𝒑𝒓𝒊𝒍 𝑹𝒆𝒈𝒊𝒔𝒕𝒆𝒓 𝒏𝒐𝒘 𝒕𝒐 𝒂𝒕𝒕𝒆𝒏𝒅 𝑭𝒓𝒆𝒆 𝑫𝒆𝒎𝒐: https://lnkd.in/dR3gr3-4 𝑶𝑹 𝑱𝒐𝒊𝒏 𝒕𝒉𝒆 𝑾𝒉𝒂𝒕𝒔𝑨𝒑𝒑 𝒈𝒓𝒐𝒖𝒑 𝒇𝒐𝒓 𝒕𝒉𝒆 𝒍𝒂𝒕𝒆𝒔𝒕 𝑼𝒑𝒅𝒂𝒕𝒆: https://lnkd.in/dYbwbgPs : Follow Pavan Gaikwad for more helpful content. #SoftwareTesting #AutomationTesting #Java #OOP #SDET #TestAutomation #QualityEngineering
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