# Build a restaurant discovery feature with TripAdvisor Gateway This tutorial shows you how to build a complete "restaurants near me" feature — from coordinates to fully enriched location cards with photos, ratings, and reviews — using just two API calls. --- ## What you'll build A restaurant discovery flow that: 1. Takes a latitude/longitude coordinate 2. Returns nearby restaurants with ratings and addresses 3. Fetches full details, photos, and reviews for each result 4. Displays everything needed for a rich location card This is the exact pattern used by travel apps, map integrations, and booking platforms. --- ## Step 1 — Find restaurants near a coordinate Use `/nearby` with a lat/long pair and filter by `restaurants`: **cURL:** ```bash curl "https://tripadvisor-gateway-api1.p.rapidapi.com/nearby?latLong=-22.9068,-43.1729&category=restaurants&radius=1&radiusUnit=km&X-TripAdvisor-Key=YOUR_TA_KEY" \ -H "X-RapidAPI-Key: YOUR_RAPIDAPI_KEY" ``` **JavaScript:** ```javascript async function getNearbyRestaurants(lat, lng) { const res = await fetch( `https://tripadvisor-gateway-api1.p.rapidapi.com/nearby?latLong=${lat},${lng}&category=restaurants&radius=1&radiusUnit=km&X-TripAdvisor-Key=YOUR_TA_KEY`, { headers: { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY" } } ); const data = await res.json(); return data.data; // array of up to 10 nearby restaurants } const restaurants = await getNearbyRestaurants(-22.9068, -43.1729); console.log(restaurants.map(r => r.name)); ``` **Python:** ```python import requests def get_nearby_restaurants(lat, lng, radius_km=1): params = { "latLong": f"{lat},{lng}", "category": "restaurants", "radius": radius_km, "radiusUnit": "km", "X-TripAdvisor-Key": "YOUR_TA_KEY" } headers = { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY" } data = requests.get( "https://tripadvisor-gateway-api1.p.rapidapi.com/nearby", headers=headers, params=params ).json() return data.get("data", []) restaurants = get_nearby_restaurants(-22.9068, -43.1729) for r in restaurants: print(r["location_id"], r["name"]) ``` **Example response:** ```json { "data": [ { "location_id": "323301", "name": "Taberna de Haro", "distance": "0.3", "bearing": "northwest", "address_obj": { "street1": "Rua Domingos Ferreira, 269", "city": "Rio de Janeiro", "address_string": "Rua Domingos Ferreira, 269, Rio de Janeiro" } } ] } ``` --- ## Step 2 — Enrich each result with full details Use `/location/full` to get details + photos + reviews for each `location_id` in a single call: **JavaScript:** ```javascript async function getLocationCard(locationId) { const res = await fetch( `https://tripadvisor-gateway-api1.p.rapidapi.com/location/full?locationId=${locationId}&X-TripAdvisor-Key=YOUR_TA_KEY`, { headers: { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY" } } ); return res.json(); } // Enrich all nearby results const enriched = await Promise.all( restaurants.map(r => getLocationCard(r.location_id)) ); ``` **Python:** ```python def get_location_card(location_id): params = { "locationId": location_id, "X-TripAdvisor-Key": "YOUR_TA_KEY" } headers = { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY" } return requests.get( "https://tripadvisor-gateway-api1.p.rapidapi.com/location/full", headers=headers, params=params ).json() # Enrich all nearby results cards = [get_location_card(r["location_id"]) for r in restaurants] ``` **Each card response contains:** ```json { "location_id": "323301", "details": { "name": "Taberna de Haro", "rating": "3.5", "num_reviews": "412", "description": "Spanish restaurant in Copacabana...", "price_level": "$$ - $$$", "cuisine": [{ "name": "Spanish" }, { "name": "Mediterranean" }], "hours": { "weekday_text": ["Monday: 12:00 PM - 11:00 PM"] }, "phone": "+55 21 2255-0000", "web_url": "https://www.tripadvisor.com/Restaurant_Review-..." }, "photos": { "data": [ { "images": { "medium": { "url": "https://media-cdn.tripadvisor.com/..." }, "large": { "url": "https://media-cdn.tripadvisor.com/..." } } } ] }, "reviews": { "data": [ { "rating": 4, "title": "Good food, slow service", "text": "The gambas were excellent...", "trip_type": "Couples", "travel_date": "2024-11" } ] }, "_meta": { "calls_made": 3 } } ``` --- ## Step 3 — Build the location card UI Here's a minimal HTML card using the data above: ```html

{details.name}

⭐ {details.rating} · {details.num_reviews} reviews

{details.price_level} · {details.cuisine[0].name}

{details.address_obj.address_string}

"{reviews.data[0].text}" — {reviews.data[0].trip_type} traveler, {reviews.data[0].travel_date}

``` --- ## Complete flow summary ``` User location (lat, lng) ↓ GET /nearby?latLong=...&category=restaurants ↓ Up to 10 location_ids returned ↓ GET /location/full?locationId=... (one per result) ↓ Full card: name · rating · photos · reviews · hours · price ``` **Total API requests used:** 1 (nearby) + N (one `/full` per result shown) --- ## Optimizations - **Lazy loading** — Call `/nearby` first, show basic cards, then load `/location/full` only when the user taps a card - **Language localization** — Add `&language=pt` for Portuguese results, `¤cy=BRL` for Brazilian Real prices - **Category switching** — Swap `category=restaurants` for `hotels` or `attractions` to reuse the same pattern - **Radius tuning** — Start with `radius=1&radiusUnit=km` for dense urban areas, expand to 5–10km for suburban --- ## Add AI Intelligence to each card (Ultra+) On Ultra or Mega plans, add one more call per location to get a reputation score, trend, and alerts: ```javascript const intel = await fetch( `https://tripadvisor-gateway-api1.p.rapidapi.com/location/intelligence?locationId=${locationId}&reviews=10&X-TripAdvisor-Key=YOUR_TA_KEY`, { headers: { "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY" } } ).then(r => r.json()); // Now you can show: // Score: 84/100 | Trend: ↑ IMPROVING | ⚠️ 1 alert ``` Full API documentation: [https://dinholc.github.io/tripadvisor-gateway-api](https://dinholc.github.io/tripadvisor-gateway-api)