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blog content: building-elasticsearch-apis-with-fastapi-websockets (#472)
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‎supporting-blog-content/building-elasticsearch-apis-with-fastapi-websockets/README.md

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# Quickstart
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Follow these steps to set up and run the FastAPI API:
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1. **Create a virtual environment:**
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```bash
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python3 -m venv venv
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```
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2. **Activate the virtual environment:**
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- On macOS/Linux:
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```bash
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source venv/bin/activate
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```
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- On Windows:
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```bash
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venv\Scripts\activate
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```
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3. **Install dependencies:**
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```bash
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pip install -r requirements.txt
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```
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4. **Run the API with uvicorn:**
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```bash
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uvicorn main:app --reload
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```
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The API will be available at [http://localhost:8000](http://localhost:8000)
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## Credentials
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When you run the API, you will be prompted to insert your Elasticsearch endpoint and API key using `getpass`. These credentials are required to connect to your Elasticsearch instance.
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At the terminal, you will see prompts like this to insert your credentials:
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```
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Insert the Elasticsearch endpoint here:
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Insert the Elasticsearch API key here:
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```

‎supporting-blog-content/building-elasticsearch-apis-with-fastapi-websockets/elasticsearch_bulk_request.txt

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POST products/_bulk
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{"index":{}}
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{"product_name": "iPhone 15 Pro", "price": 999.99, "description": "Latest flagship smartphone with titanium design, A17 Pro chip, and advanced camera system"}
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{"index":{}}
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{"product_name": "MacBook Pro 14-inch", "price": 1999.99, "description": "Professional laptop with M3 chip, Liquid Retina XDR display, and up to 22-hour battery life"}
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{"index":{}}
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{"product_name": "AirPods Pro 2nd Gen", "price": 249.99, "description": "Wireless earbuds with active noise cancellation, spatial audio, and USB-C charging case"}
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{"index":{}}
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{"product_name": "iPad Air", "price": 599.99, "description": "Versatile tablet with M1 chip, 10.9-inch Liquid Retina display, and Apple Pencil support"}
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{"index":{}}
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{"product_name": "Apple Watch Series 9", "price": 399.99, "description": "Advanced smartwatch with health monitoring, fitness tracking, and always-on Retina display"}
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{"index":{}}
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{"product_name": "Samsung Galaxy S24 Ultra", "price": 1199.99, "description": "Premium Android smartphone with S Pen, 200MP camera, and AI-powered features"}
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{"index":{}}
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{"product_name": "Dell XPS 13", "price": 1299.99, "description": "Ultra-portable laptop with Intel Core i7, 13.4-inch InfinityEdge display, and premium build"}
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{"index":{}}
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{"product_name": "Sony WH-1000XM5", "price": 399.99, "description": "Premium noise-canceling headphones with 30-hour battery and exceptional audio quality"}
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{"index":{}}
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{"product_name": "Nintendo Switch OLED", "price": 349.99, "description": "Hybrid gaming console with vibrant OLED screen, enhanced audio, and portable design"}
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{"index":{}}
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{"product_name": "Kindle Paperwhite", "price": 139.99, "description": "E-reader with 6.8-inch glare-free display, waterproof design, and weeks of battery life"}
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{"index":{}}
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{"product_name": "Google Pixel 8 Pro", "price": 999.99, "description": "AI-powered smartphone with advanced computational photography and 7 years of updates"}
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{"index":{}}
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{"product_name": "Microsoft Surface Pro 9", "price": 1099.99, "description": "2-in-1 laptop tablet with Intel Core processors, detachable keyboard, and Surface Pen support"}
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{"index":{}}
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{"product_name": "Dyson V15 Detect", "price": 749.99, "description": "Powerful cordless vacuum with laser dust detection and intelligent suction adjustment"}
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{"index":{}}
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{"product_name": "Fitbit Versa 4", "price": 199.99, "description": "Health and fitness smartwatch with GPS, heart rate monitoring, and 6+ day battery"}
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{"index":{}}
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{"product_name": "Bose QuietComfort 45", "price": 329.99, "description": "Wireless noise-canceling headphones with balanced sound and 24-hour battery life"}
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{"index":{}}
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{"product_name": "Tesla Model Y", "price": 47190.00, "description": "Electric SUV with autopilot, 330-mile range, and minimalist interior design"}
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{"index":{}}
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{"product_name": "Instant Pot Duo 7-in-1", "price": 99.99, "description": "Multi-use pressure cooker that replaces 7 kitchen appliances with smart programming"}
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{"index":{}}
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{"product_name": "LG OLED C3 55-inch TV", "price": 1499.99, "description": "4K OLED smart TV with perfect blacks, vibrant colors, and gaming-optimized features"}
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{"index":{}}
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{"product_name": "Vitamix A3500", "price": 549.99, "description": "Professional-grade blender with preset programs, self-cleaning, and 10-year warranty"}
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{"index":{}}
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{"product_name": "Herman Miller Aeron Chair", "price": 1395.00, "description": "Ergonomic office chair with breathable mesh, lumbar support, and 12-year warranty"}
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{"index":{}}
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{"product_name": "Canon EOS R5", "price": 3899.99, "description": "Professional mirrorless camera with 45MP sensor, 8K video, and advanced autofocus"}
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{"index":{}}
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{"product_name": "Sonos Arc Soundbar", "price": 899.99, "description": "Premium soundbar with Dolby Atmos, voice control, and seamless music streaming"}
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{"index":{}}
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{"product_name": "Peloton Bike+", "price": 2495.00, "description": "Interactive exercise bike with rotating HD touchscreen and live fitness classes"}
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{"index":{}}
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{"product_name": "Roomba j7+", "price": 849.99, "description": "Smart robot vacuum with object avoidance, self-emptying base, and app control"}
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{"index":{}}
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{"product_name": "KitchenAid Stand Mixer", "price": 379.99, "description": "Iconic stand mixer with 10-speed control, tilt-head design, and multiple attachments"}

‎supporting-blog-content/building-elasticsearch-apis-with-fastapi-websockets/index.html

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>TechStore - Product Search</title>
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</head>
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<body>
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<header>
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<h1>🛍️ TechStore - Find Your Perfect Product</h1>
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</header>
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<main>
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<form onsubmit="event.preventDefault(); searchProducts();">
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<fieldset>
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<legend>Product Search</legend>
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<p>
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<label for="searchQuery">Search Products:</label><br />
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<input
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type="text"
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id="searchQuery"
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placeholder="Search for phones, laptops, headphones..."
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size="50"
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required />
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<button type="submit">🔍 Search</button>
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</p>
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</fieldset>
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</form>
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<fieldset>
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<legend>Live Notifications</legend>
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<p id="status">🟡 Connecting to live notifications...</p>
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</fieldset>
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<section id="searchResults">
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<h2>Search Results</h2>
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<blockquote>
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<em>🔍 Enter a search term above to find products</em>
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</blockquote>
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</section>
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</main>
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<!-- HTML Dialog for notifications -->
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<dialog id="notificationDialog">
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<fieldset>
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<legend>🔔 Live Search Activity</legend>
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<p id="notificationMessage"></p>
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<p>
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<button onclick="closeNotification()" autofocus>OK</button>
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</p>
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</fieldset>
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</dialog>
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<script>
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let ws = null;
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let sessionId = null;
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window.onload = function () {
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sessionId = "session_" + Date.now();
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connectWebSocket();
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};
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function connectWebSocket() {
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const statusDiv = document.getElementById("status");
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ws = new WebSocket("ws://localhost:8000/ws");
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ws.onopen = function () {
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statusDiv.innerHTML =
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"🟢 Connected - You will see when others search for products";
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console.log("Connected to WebSocket");
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};
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ws.onmessage = function (event) {
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try {
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const notification = JSON.parse(event.data);
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if (notification.type === "search") {
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showSearchNotification(notification);
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}
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} catch (error) {
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console.error("Error parsing notification:", error);
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}
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};
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ws.onclose = function () {
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statusDiv.innerHTML = "🔴 Disconnected from live notifications";
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console.log("Disconnected from WebSocket");
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};
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ws.onerror = function (error) {
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statusDiv.innerHTML = "❌ Connection error";
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console.error("WebSocket error:", error);
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};
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}
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function showSearchNotification(notification) {
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// Skip notifications from the same session (same browser window)
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if (notification.session_id === sessionId) {
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return;
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}
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const dialog = document.getElementById("notificationDialog");
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const messageElement = document.getElementById("notificationMessage");
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messageElement.innerHTML = `<p><strong>Hot search alert!</strong> Other users are looking for <em>"${notification.query}"</em> right now.</p>`;
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dialog.showModal();
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}
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function closeNotification() {
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const dialog = document.getElementById("notificationDialog");
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dialog.close();
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}
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async function searchProducts() {
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const query = document.getElementById("searchQuery").value.trim();
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const resultsDiv = document.getElementById("searchResults");
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if (!query) {
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resultsDiv.innerHTML = `
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<h2>Search Results</h2>
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<blockquote>
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<strong>⚠️ Please enter a search term</strong>
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</blockquote>
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`;
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return;
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}
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resultsDiv.innerHTML = `
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<h2>Search Results</h2>
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<blockquote>
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<em>🔍 Searching TechStore inventory...</em>
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</blockquote>
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`;
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try {
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const response = await fetch(
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`/search?q=${encodeURIComponent(
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query
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)}&session_id=${encodeURIComponent(sessionId)}`
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);
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const data = await response.json();
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if (response.ok) {
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displaySearchResults(data);
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} else {
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throw new Error(data.error || "Search failed");
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}
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} catch (error) {
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resultsDiv.innerHTML = `
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<h2>Search Results</h2>
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<fieldset>
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<legend>❌ Search Error</legend>
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<p><strong>Error:</strong> ${error.message}</p>
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</fieldset>
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`;
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}
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}
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function displaySearchResults(data) {
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const resultsDiv = document.getElementById("searchResults");
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if (data.results.length === 0) {
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resultsDiv.innerHTML = `
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<h2>Search Results</h2>
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<fieldset>
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<legend>❌ No products found</legend>
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<p>No products match "<strong>${data.query}</strong>"</p>
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<p><em>Try searching for: iPhone, laptop, headphones, watch, etc.</em></p>
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</fieldset>
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`;
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return;
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}
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let html = `<h2>✅ Found ${data.total} products for "${data.query}"</h2>`;
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data.results.forEach((product) => {
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html += `
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<fieldset>
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<legend><strong>${
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product.product_name
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}</strong></legend>
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<p><big>💰 $${product.price.toFixed(2)}</big></p>
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<p>${product.description}</p>
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</fieldset>
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`;
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});
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resultsDiv.innerHTML = html;
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}
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</script>
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</body>
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</html>

‎supporting-blog-content/building-elasticsearch-apis-with-fastapi-websockets/inegst_data.py

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import json
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import os
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from elasticsearch import Elasticsearch
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es_client = Elasticsearch(
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hosts=[os.environ["ELASTICSEARCH_ENDPOINT"]],
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api_key=os.environ["ELASTICSEARCH_API_KEY"],
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)
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PRODUCTS_INDEX = "products"
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def create_products_index():
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try:
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mapping = {
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"mappings": {
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"properties": {
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"product_name": {"type": "text", "analyzer": "standard"},
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"price": {"type": "float"},
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"description": {"type": "text", "analyzer": "standard"},
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}
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}
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}
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es_client.indices.create(index=PRODUCTS_INDEX, body=mapping)
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print(f"Index {PRODUCTS_INDEX} created successfully")
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except Exception as e:
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print(f"Error creating index: {e}")
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def load_products_from_ndjson():
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try:
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if not os.path.exists("products.ndjson"):
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print("Error: products.ndjson file not found!")
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return
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products_loaded = 0
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with open("products.ndjson", "r") as f:
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for line in f:
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if line.strip():
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product_data = json.loads(line.strip())
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es_client.index(index=PRODUCTS_INDEX, body=product_data)
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products_loaded += 1
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print(f"Successfully loaded {products_loaded} products into Elasticsearch")
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except Exception as e:
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print(f"Error loading products: {e}")
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if __name__ == "__main__":
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create_products_index()
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load_products_from_ndjson()

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