All About Interview Of Devloper

Here’s a structured development task breakdown for building a Wireshark C plugin that decodes payload data by calling an external API and displays it in the packet detail tree. Project Scope Create a C-based dissector plugin for Wireshark. The plugin will: Detect packets matching a custom condition (e.g., specific IP/Port or protocol signature). Extract payload data from the packet. Send this data to an external REST API for decoding. Parse the API response and display it as hierarchical fields in the Wireshark packet detail tree. Key Technical Considerations Wireshark’s dissector thread is not designed for blocking calls — calling an API directly inside packet dissection would freeze the UI. Solution: Implement an asynchronous model : Option 1: Maintain a local cache/database pre-filled from the API. Option 2: Use a background thread to fetch API data, store in memory, and refresh the view when available. Database integration (optional) — store API results in ...

Here’s what I found after checking Wireshark’s official capabilities and development documentation about plugin support—especially regarding integrations with databases: 1. Wireshark Plugin Support Overview Wireshark plugins are primarily used to extend protocol dissection functionality. They come in two flavors: C plugins (compiled dissectors) : Deep integration, high performance, access to Wireshark’s internal APIs and UI. Lua scripts : Easier to write and iterate faster. Great for prototyping, taps (post-dissectors), custom menus, and more . 2. Lua Extension Mechanism & Limitations Wireshark includes an embedded Lua interpreter. Supported Lua versions: Early versions: Lua 5.1 & 5.2 Wireshark 4.4 and later: Lua 5.3 & 5.4 . Lua plugins can register: Dissectors , listener taps , file readers/writers , and custom menus/statistics . Lua does not natively include any database libraries—but you can: Use require() to load shared Lua modules or C-wrappe...

Got it — you want an ideation PPT for your AI-based document Q&A chatbot idea. I’ll make you a clear, professional slide structure you can directly put into PowerPoint or Google Slides. AI Document Q&A Chatbot – Ideation Deck Slide 1 – Title "AI-Powered Document Intelligence Chatbot" Ask Anything. Get Instant Answers from Your Documents. Image: AI + document icons Tagline: “Your PDF, Excel, Word — Now Speak Your Language” Slide 2 – Problem Statement Current Challenges Searching through long PDF, Excel, Word docs is slow and inefficient. Manual searching leads to missed information. Teams waste hours in finding the right paragraph, cell, or page. Difficult to integrate across multiple file formats. Slide 3 – Opportunity Every business works with large volumes of documents. Faster information retrieval = faster decisions. Knowledge should be instantly available to anyone in the organization. AI can bridge the gap between data storage and dat...

from sentence_transformers import SentenceTransformer # Use a better embedding model embed_model = SentenceTransformer("BAAI/bge-base-en-v1.5") # larger, better accuracy embeddings = embed_model.encode(texts, normalize_embeddings=True)

Got it — you want to create a local AI chatbot that can answer questions based on the content of an Excel file you provide, and you’ll be using VS Code to build it. I’ll walk you through the process step-by-step and then give you a working Python example . Plan 1. Tech Stack Language: Python Editor: VS Code Libraries: pandas → for reading Excel openpyxl → Excel engine for .xlsx langchain (optional) → for question-answering logic ollama / transformers → for local AI model (you mentioned earlier you might use ollama gpt-oss:20b ) 2. Basic Workflow Read Excel File → Load all data into Python using pandas . Convert Data to Text → Transform rows into a searchable text format. Ask Question → Take the user’s query. Search for Relevant Data → Use either: Simple : Keyword search in dataframe Advanced : Embeddings + vector search for semantic meaning Generate Answer → Feed the found data to the AI model to create a natural answer. 3. Example — Simple ...

Got it — here’s your Automobile Infotainment AI case study written in a detailed yet concise, human-friendly format , but still keeping the structured slide-style flow so it’s ready for presentation or proposal use. Revolution of AI in Automobile Infotainment Broad Market Trends AI is reshaping how we experience cars. Infotainment systems are evolving from basic media consoles into intelligent, connected hubs that personalize every journey. Personalized Experience – AI tailors playlists, navigation routes, and climate settings to each driver. Voice-First Interfaces – Natural, hands-free voice commands reduce distraction. Predictive Analytics – Anticipates needs like fuel stops, maintenance, or preferred routes. Connected Car Ecosystems – Syncs with IoT devices, smart homes, and cloud services. Driver Monitoring – Detects fatigue or unsafe driving patterns. Augmented Navigation – Real-time hazard detection and AR guidance. Possibilities AI-assisted over-the-air (O...

Yes, ✅ you can do this directly in Excel using a formula — no code or external tool required . Here’s how you can achieve the same logic using a formula in Column N of the "Icon Tracker" sheet: 🧠 What You Want: For each row: Check if value in Column M exists in Column G of the "ICON management" sheet. If not found and the value is not "NA" , show: "Icon not present in management Sheet" . If value is "NA" → leave blank . ✅ Excel Formula for Column N (e.g., N2): =IF(OR(M2="NA", ISNUMBER(MATCH(M2, 'ICON management'!G:G, 0))), "", "Icon not present in management Sheet") 💡 Explanation: Part Meaning M2="NA" Checks if current row's value in Column M is "NA" (case-sensitive, use LOWER() for case-insensitive). MATCH(M2, 'ICON management'!G:G, 0) Looks for M2's value in Column G of "ICON management". Returns row number if fo...

Bdbjfjjfnnfnf

Great choice! ✅ ClosedXML is: 💯 Free for commercial and non-commercial use (MIT License). 🧼 Easier to use than EPPlus. 📁 Works with .xlsx files only. 🎯 Goal Recap We will use ClosedXML to: Open two Excel files. In File 1 , sheet "Icon Tracker" , read values from Column M . In File 2 , sheet "ICON management" , read values from Column G . For each value in Column M: If it’s not found in Column G → write "Icon not present in management Sheet" in Column N (same row). Save File 1 with the updates. 📦 Install ClosedXML In Package Manager Console : Install-Package ClosedXML 📄 ExcelService.cs Using ClosedXML using ClosedXML.Excel; using System; using System.Collections.Generic; using System.IO; namespace WpfIconCheckerApp.Models { public class ExcelService { public static string CompareExcelFiles(string file1Path, string file2Path) { try { using var workbook1 = new XLWorkbo...

Perfect! ✅ Let's replace Microsoft.Office.Interop.Excel with EPPlus , which: Doesn't require Microsoft Excel to be installed. Is much faster and more stable for server/desktop apps. 🔧 Updated Requirements Read 2 Excel files . In File 1 , "Icon Tracker" sheet → get Column M values. In File 2 , "ICON management" sheet → get Column G values. If value in Column M is not in Column G , write "Icon not present in management Sheet" in Column N . Use EPPlus (works on .xlsx only). 📦 Install EPPlus via NuGet Run this in the NuGet Package Manager: Install-Package EPPlus 🧠 Updated ExcelService.cs using EPPlus using OfficeOpenXml; using System.Collections.Generic; using System.IO; namespace WpfIconCheckerApp.Models { public class ExcelService { public static string CompareExcelFiles(string file1Path, string file2Path) { ExcelPackage.LicenseContext = LicenseContext.NonCommercial; try ...

Here’s a WPF application using MVVM pattern in C# that: Reads two Excel files . Compares values in Column M of the "Icon Tracker" sheet in the first Excel file with Column G of the "ICON management" sheet in the second Excel file. If a value from Column M is not present in Column G , it writes "Icon not present in management Sheet" in the corresponding Column N of the first Excel file. 🛠 Technologies Used C# WPF (MVVM) Microsoft.Office.Interop.Excel 📁 Folder Structure WpfIconCheckerApp/ ├── ViewModels/ │ └── MainViewModel.cs ├── Views/ │ └── MainWindow.xaml ├── Models/ │ └── ExcelService.cs ├── App.xaml ├── MainWindow.xaml.cs └── WpfIconCheckerApp.csproj 1️⃣ MainWindow.xaml (View) <Window x:Class="WpfIconCheckerApp.MainWindow" xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation" xmlns:d="http://schemas.microsoft.com/expression/blend/2008" xmlns:x=...

The ADB command string to invoke Google Assistant is: adb shell am start -a com.google.android.googlequicksearchbox.action.ASSIST You can run this in C# by passing it as the argument string to adb .

To export the DataGrid content to an Excel (.xlsx) file , we’ll use ClosedXML — a popular .NET library for working with Excel files. ✅ Step-by-Step Update 📦 1. Install ClosedXML NuGet Package Run this in Package Manager Console : Install-Package ClosedXML 🧠 2. Update ViewModel ( MainViewModel.cs ) Add a new command: public ICommand ExportToExcelCommand => new RelayCommand(ExportToExcel); Add this method to MainViewModel : private void ExportToExcel() { var dialog = new SaveFileDialog { Filter = "Excel Workbook (*.xlsx)|*.xlsx" }; if (dialog.ShowDialog() == true) { using var workbook = new ClosedXML.Excel.XLWorkbook(); var worksheet = workbook.Worksheets.Add("Command Results"); worksheet.Cell(1, 1).Value = "Command ID"; worksheet.Cell(1, 2).Value = "ADB Command"; worksheet.Cell(1, 3).Value = "CAN Signal"; worksheet.Cell(1, 4).Value = "Expected Value";...

using System; using System.Runtime.InteropServices; using Excel = Microsoft.Office.Interop.Excel; namespace ExcelRedToBlack {     class Program     {         static void Main(string[] args)         {             Console.WriteLine("Enter full path to the Excel file:");             string filePath = Console.ReadLine();             if (string.IsNullOrWhiteSpace(filePath))             {                 Console.WriteLine("Invalid file path.");                 return;             }             Excel.Application excelApp = null;             Excel.Workbook workbook = null;             try         ...

🔄 Figma REST API – Version History ✅ Endpoint GET https://api.figma.com/v1/files/{file_key}/versions This endpoint retrieves the list of named versions for a given file. --- 🔐 Authentication Required Use a Personal Access Token (PAT) as a Bearer token in the Authorization header. You can create a PAT from: https://www.figma.com/developers/api --- 📌 How to Get file_key You get it from the Figma file URL: https://www.figma.com/file/<file_key>/<filename> Example: URL: https://www.figma.com/file/abc123XYZ/Design-v1   → file_key = abc123XYZ --- 📥 Example Request (with curl) curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \      https://api.figma.com/v1/files/abc123XYZ/versions --- ✅ Example Response {   "versions": [     {       "id": "4452:4",       "created_at": "2025-07-25T10:00:00Z",       "label": "Wireframe Start",       "description": "Basic layout",     ...

To export layers as images from Figma using the REST API , you use the GET Image endpoint . ✅ Step-by-Step: Export Layers as Images 🔑 Prerequisites: Figma File Key – from the file URL: https://www.figma.com/file/**FILE_KEY**/... Node IDs – the layer(s) you want to export Personal Access Token – from Figma account settings 🧪 1. Get Node IDs (Layer IDs) Endpoint: GET https://api.figma.com/v1/files/{file_key} Returns a full file structure ( document ) Traverse the JSON to find id of the nodes/layers you want to export (e.g., text, image, button, frame) Example node ID: "25:12" 🖼️ 2. Export Node as Image Endpoint: GET https://api.figma.com/v1/images/{file_key} Query Parameters: ids : Comma-separated node IDs format : png , jpg , or svg scale : optional, defaults to 1 (can be 2 for high-res) use_absolute_bounds : optional for exporting only visible area Example Request: GET https://api.figma.com/v1/images/AbCDeFGHIjkL?ids=25:12&format=pn...

 Here's the PowerPoint slide data using only the first and second responses (which covered Figma REST API accessible data and a categorized API list): --- 🎯 Slide 1: Title Slide Title: Accessing Figma Data via REST API Subtitle: What’s Possible and What’s Not with Figma’s API --- ✅ Slide 2: What You Can Access via Figma REST API File & Design Data (Read-only): File metadata (name, modified date, version) Document structure (pages, frames, groups, nodes) Colors, fonts, layout, vectors, strokes, effects Local & team components Export images (PNG, JPG, SVG, PDF) Comments (read, post, resolve) Version history Project and team data (for Org accounts) --- ❌ Slide 3: What You Cannot Access via API Limitations: No write/edit of nodes or layout Cannot simulate or control prototypes No real-time collaboration info (like cursors) No plugin execution Cannot access plugin-specific or private data No access to interactions/animations execution --- 🌐 Slide 4: Key API Endpoints Purpose E...