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Swiggy Dineout Restaurants Scraper API

The Swiggy Dineout Restaurants Scraper API revolutionizes restaurant extraction, delivering structured restaurant datasets with zero hassle. Bypass parsing complexities and IP blocks to access comprehensive restaurant crawler data via seamless swiggy apis integration. Build rich restaurants dataset for analytics, pricing insights, and market research effortlessly.

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Что можно построить с помощью Swiggy Dineout Restaurants Scraper API Scraper?

With our restaurant extraction tools, create dynamic restaurant datasets for competitive analysis, build location-based apps using real-time Swiggy Dineout data, and automate restaurant crawler workflows for menu pricing tracking and customer review aggregation across cities.

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Real-Time Restaurant Data

Fetch fresh restaurant datasets instantly via REST endpoints, perfect for Python scripts or Node.js apps needing up-to-date JSON from Swiggy Dineout listings.

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Structured JSON Output

Get clean, parse-ready restaurant extraction results with fields like ratings, menus, and locations, eliminating manual data cleaning for faster insights.

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Scalable Restaurant Crawler

Handle thousands of requests asynchronously, building massive restaurants datasets without rate limits or downtime using our robust swiggy apis backend.

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High Accuracy Extraction

99% precise restaurant datasets with smart parsing, ensuring reliable data for ML models, dashboards, or business intelligence tools.

Доверие дата-ориентированных команд по всему миру

Используется в аналитике, исследованиях, мониторинге и growth-командах.

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Доступные Swiggy Dineout Restaurants Scraper API скраперы

Получайте самые востребованные типы данных Swiggy Dineout Restaurants Scraper API — всегда структурированные, единообразные и готовы к работе.

extraction restaurant

Extract detailed profiles of Swiggy Dineout restaurants including locations and offerings via simple API calls.

Метод скрапинга:
  • restaurant_id
  • name
  • address
  • cuisine
  • rating
  • price_range
  • images

restaurant dataset

Compile comprehensive restaurant datasets from searches, covering multiple cities and categories.

Метод скрапинга:
  • name
  • city
  • area
  • average_cost
  • reviews_count
  • menu_url
  • contact_info

restaurant datasets

Generate bulk restaurant datasets with historical trends and competitor comparisons.

Метод скрапинга:
  • restaurant_id
  • name
  • rating
  • delivery_time
  • offers
  • photos
  • user_ratings

restaurants dataset

Build aggregated restaurants dataset for nationwide Swiggy Dineout coverage and analytics.

Метод скрапинга:
  • chain_name
  • outlets_count
  • avg_rating
  • cuisines
  • pricing_history
  • media_urls

restaurant crawler

Automated restaurant crawler endpoint for continuous monitoring of listings and updates.

Метод скрапинга:
  • name
  • status
  • last_updated
  • menu_items
  • reviews
  • engagement_metrics

restaurant extraction

Precise restaurant extraction pulling reviews, menus, and seller details from Swiggy Dineout.

Метод скрапинга:
  • restaurant_name
  • owner_info
  • verified_status
  • comments
  • pricing
  • variants

Методы обхода Swiggy Dineout Restaurants Scraper API

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API-скрапинг (для разработчиков)

Integrate via REST API for full control in Python, Node.js, or any backend stack.

  • XCrawl
    Async Requests
    Scale restaurant extraction with asynchronous calls for high-volume restaurant datasets.
  • XCrawl
    SDK Support
    Use official Python and Node.js SDKs for quick swiggy apis integration.
  • XCrawl
    JSON Webhooks
    Receive real-time restaurant crawler updates via customizable webhooks.
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No-code скрапинг (для Ops и growth команд)

Use our intuitive dashboard for point-and-click restaurant data collection.

  • XCrawl
    Visual Query Builder
    Select fields visually to build custom restaurant datasets without code.
  • XCrawl
    Automated Scheduling
    Schedule daily restaurant extraction runs for fresh restaurants dataset.
  • XCrawl
    CSV/Excel Export
    Download processed data instantly in spreadsheet formats for analysis.

Примеры кода

Получайте публикации Swiggy Dineout Restaurants Scraper API и данные об авторах за секунды с помощью простого API-запроса.

Ввод
Shell
curl -X POST https://xcrawl.com -H "Authorization: YOU_TOKEN" -H "Content-Type: application/json" -d "{\"geo\":\"US\",\"context\":{\"keyword_list\":[{\"keyword\":\"Apple\"}],\"start_page\":1,\"pages\":1},\"source\":\"amazon_search\"}"
Результат
Json
{
"result":[
{
"content":{
"url":"https://www.amazon.com/s?k=Apple&page=1"
"page":1
"query":"Apple"
"results":{
"organic":[
{
"pos":1
"url":"https://www.amazon.com/sspa/click?ie=UTF8&spc=MTo1NTU4MDIyNzE4MTQ0NDk1OjE3NjM0NDg1NjM6c3BfYXRmOjMwMDg0MTIyMDE1MTYwMjo6MDo6&url=%2FApple-11-inch-Intelligence-Display-All-Day%2Fdp%2FB0DZ73HCJZ%2Fref%3Dsr_1_1_sspa%3Fdib%3DeyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs%26dib_tag%3Dse%26keywords%3DApple%26qid%3D1763448563%26sr%3D8-1-spons%26sp_csd%3Dd2lkZ2V0TmFtZT1zcF9hdGY%26psc%3D1"
"asin":"B0DZ73HCJZ"
"price":499.99
"title":"SponsoredSponsored You’re seeing this ad based on the product’s relevance to your search query.Leave ad feedback AppleiPad Air 11-inch with M3 chip Built for Apple Intelligence, Liquid Retina Display, 128GB, 12MP Front/Back Camera, Wi-Fi 6E, Touch ID, All-Day Battery Life — Purple"
"rating":4.8
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/71b-vc2xzlL._AC_UY218_.jpg"
"best_seller":false
"price_upper":499.99
"is_sponsored":false
"sales_volume":"1K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":599
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
{
"pos":2
"url":"https://www.amazon.com/sspa/click?ie=UTF8&spc=MTo1NTU4MDIyNzE4MTQ0NDk1OjE3NjM0NDg1NjM6c3BfYXRmOjMwMDg0MTI5NzA2MjkwMjo6MDo6&url=%2FApple-Bluetooth-Headphones-Personalized-Effortless%2Fdp%2FB0DGHMNQ5Z%2Fref%3Dsr_1_2_sspa%3Fdib%3DeyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs%26dib_tag%3Dse%26keywords%3DApple%26qid%3D1763448563%26sr%3D8-2-spons%26sp_csd%3Dd2lkZ2V0TmFtZT1zcF9hdGY%26psc%3D1"
"asin":"B0DGHMNQ5Z"
"price":117
"title":"SponsoredSponsored You’re seeing this ad based on the product’s relevance to your search query.Leave ad feedback AppleAirPods 4 Wireless Earbuds, Bluetooth Headphones, Personalized Spatial Audio, Sweat and Water Resistant, USB-C Charging Case, H2 Chip, Up to 30 Hours of Battery Life, Effortless Setup for iPhone"
"rating":4.5
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/61iBtxCUabL._AC_UY218_.jpg"
"best_seller":false
"price_upper":117
"is_sponsored":false
"sales_volume":"10K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":129
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
{
"pos":3
"url":"https://www.amazon.com/Apple-MX542LL-A-AirTag-Pack/dp/B0D54JZTHY/ref=sr_1_3?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-3"
"asin":"B0D54JZTHY"
"price":79.98
"title":"AppleAirTag 4 Pack. Keep Track of and find Your Keys, Wallet, Luggage, Backpack, and More. Simple one-tap Set up with iPhone or iPad"
"rating":4.7
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/61bMNCeAUAL._AC_UY218_.jpg"
"best_seller":false
"price_upper":79.98
"is_sponsored":false
"sales_volume":"10K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":99
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
{
"pos":4
"url":"https://www.amazon.com/Apple-MX532LL-A-AirTag/dp/B0CWXNS552/ref=sr_1_4?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-4"
"asin":"B0CWXNS552"
"price":17.97
"title":"AppleAirTag. Keep Track of and find Your Keys, Wallet, Luggage, Backpack, and More. Simple one-tap Set up with iPhone or iPad"
"rating":4.7
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/71rP7f78eFL._AC_UY218_.jpg"
"best_seller":false
"price_upper":17.97
"is_sponsored":false
"sales_volume":"10K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":29
"shipping_information":"FREE delivery Sun, Nov 23 on $35 of items shipped by AmazonOr fastest delivery Tomorrow, Nov 19"
},
{
"pos":5
"url":"https://www.amazon.com/Apple-iPad-Pro-13-inch-M5/dp/B0FWCXMR3W/ref=sr_1_5?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-5"
"asin":"B0FWCXMR3W"
"price":2499
"title":"AppleiPad Pro 13-inch (M5): Ultra Retina XDR Display, 2TB, 12MP Front/Back Camera, LiDAR Scanner, Wi-Fi 7 with Apple N1 + 5G Cellular with C1X chip, Face ID, All-Day Battery Life — Space Black"
"rating":4.6
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/715V3wbnD6L._AC_UY218_.jpg"
"best_seller":false
"price_upper":2499
"is_sponsored":false
"sales_volume":null
"pricing_count":1
"reviews_count":16
"is_amazons_choice":false
"price_strikethrough":""
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Thu, Nov 20"
},
{
"pos":6
"url":"https://www.amazon.com/Apple-Cancellation-Translation-Headphones-High-Fidelity/dp/B0FQFB8FMG/ref=sr_1_6?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-6"
"asin":"B0FQFB8FMG"
"price":249
"title":"AppleAirPods Pro 3 Wireless Earbuds, Active Noise Cancellation, Live Translation, Heart Rate Sensing, Hearing Aid Feature, Bluetooth Headphones, Spatial Audio, High-Fidelity Sound, USB-C Charging"
"rating":4.4
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/61solmQSSlL._AC_UY218_.jpg"
"best_seller":false
"price_upper":249
"is_sponsored":false
"sales_volume":"10K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":""
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
{
"pos":7
"url":"https://www.amazon.com/Apple-2025-MacBook-13-inch-Laptop/dp/B0DZD9S5GC/ref=sr_1_7?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-7"
"asin":"B0DZD9S5GC"
"price":749.99
"title":"Apple2025 MacBook Air 13-inch Laptop with M4 chip: Built for Apple Intelligence, 13.6-inch Liquid Retina Display, 16GB Unified Memory, 256GB SSD Storage, 12MP Center Stage Camera, Touch ID; Midnight"
"rating":4.8
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/71cWZUr9SVL._AC_UY218_.jpg"
"best_seller":false
"price_upper":749.99
"is_sponsored":false
"sales_volume":null
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":999
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
{
"pos":8
"url":"https://www.amazon.com/Apple-Headphones-Cancellation-Transparency-Personalized/dp/B0DGJ7HYG1/ref=sr_1_8?dib=eyJ2IjoiMSJ9.34Y5eLJt-Syg--Dpi7ueLQwL3ml5AvPfvC0eh7LK2pKhXumC_HQT9LBvkLBiFSrOLyabiwA1DN0qC4nDUFqkGrn5VUhsdLQFYgZ3L8DIPuzIgdPdKtqxJq8diyjiiuXTCDm8kcQmj2lflrdB1g_13fvuEjweGI5mAVZVfJ83S_reyt11VBul7Fga7znbDIGVuFDGhy2lICifAICisiNT88x1w5OOasbBiPs42bcbX0Y.sYUV92XFy8V256YhUSF1FPnMdd_kkjo8lMeGBX4Y2Rs&dib_tag=se&keywords=Apple&qid=1763448563&sr=8-8"
"asin":"B0DGJ7HYG1"
"price":148.99
"title":"AppleAirPods 4 Wireless Earbuds, Bluetooth Headphones, with Active Noise Cancellation, Adaptive Audio, Transparency Mode, Personalized Spatial Audio, USB-C Charging Case, Wireless Charging, H2 Chip"
"rating":4.5
"currency":"USD"
"is_prime":false
"url_image":"https://m.media-amazon.com/images/I/61iBtxCUabL._AC_UY218_.jpg"
"best_seller":false
"price_upper":148.99
"is_sponsored":false
"sales_volume":"10K+ bought in past month"
"pricing_count":1
"reviews_count":null
"is_amazons_choice":false
"price_strikethrough":179
"shipping_information":"FREE delivery Sun, Nov 23Or fastest delivery Tomorrow, Nov 19"
},
],
"amazons_choices":[
],
},
},
},
],
},

Как работает Scraper API для Swiggy Dineout Restaurants Scraper API?

  • XCrawlИнтеллектуальная ротация IP
  • XCrawlАвтоматическое распознавание CAPTCHA
  • XCrawlHTTP-заголовки
  • XCrawlАвтоматический парсинг страниц
  • XCrawlИндивидуальная поддержка

Что может наш API для вас?

XCrawl

Управление прокси

ML-выбор и ротация прокси на основе нашего премиум-пула из 190 стран.

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AI-генерация отпечатков браузера

Уникальные HTTP-заголовки, JavaScript и отпечатки браузера позволяют эффективно противостоять динамическому контенту.

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Обход CAPTCHA

Автоматические повторы и обход CAPTCHA для бесперебойного получения данных.

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Массовое извлечение данных

Собирайте данные одновременно с нескольких страниц — до 10 000 URL за партию.

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Разные варианты доставки

Получайте данные через облачное хранилище (например, SFTP или AWSS3) либо через API.

XCrawl

Планировщик скрапинга

Настраивайте частоту автоматического сбора данных, результат будет оперативно доставлен в облако.

XCrawl

Инфраструктура без технических забот

Забудьте о ручном обслуживании прокси и построении собственной инфраструктуры скрапинга.

XCrawl

Легко масштабируется

Простая интеграция и настройка под ваши задачи.

XCrawl

Поддержка 24/7

Профессиональная помощь в случае вопросов или проблем.

XCrawl Прозрачность

Гибкая оплата

Прозрачные цены веб-скрапинга с гибкими планами подписки API. Сравнивайте стоимость извлечения данных, покупайте доступ к краулеру и начинайте бесплатно — затем масштабируйтесь по мере роста.

Месяц
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Тарифы для масштабирования

Тарифы для больших объёмов и команд с высокими требованиями и поддержкой.

Получайте более высокие лимиты, больше одновременных браузеров и приоритетную поддержку.

Связаться с отделом продаж
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Что говорят наши клиенты?

★★★★★
5.0

Perfect for building restaurant datasets – fast, accurate extraction restaurant data saved us weeks of manual work.

Raj Patel
Raj Patel
Data Analyst
★★★★★
4.9

Swiggy apis integration was seamless; our restaurant crawler now powers real-time competitor tracking.

Priya Sharma
Priya Sharma
CTO, FoodTech Startup
★★★★★
4.8

High-quality restaurants dataset with JSON fields exactly as needed – restaurant extraction excellence.

Amit Kumar
Amit Kumar
Backend Developer
★★★★★
5.0

Generated massive restaurant datasets effortlessly; the restaurant crawler handles scale perfectly.

Neha Gupta
Neha Gupta
Market Researcher
★★★★★
4.7

Restaurant extraction API transformed our pricing analysis – reliable and dataset quality is top-notch.

Vikram Singh
Vikram Singh
Product Manager
★★★★★
4.9

Easy swiggy apis setup for restaurant datasets; fast scraping without any blocks.

Sonia Mehra
Sonia Mehra
Growth Hacker
★★★★★
5.0

Clean restaurant crawler data fueled our models – accurate extraction restaurant insights.

Karan Desai
Karan Desai
ML Engineer
★★★★★
4.8

Built comprehensive restaurants dataset for dashboards; integration was a breeze.

Lakshmi Rao
Lakshmi Rao
BI Analyst
★★★★★
4.9

Restaurant datasets from this scraper are gold – precise and scalable for clients.

Rohan Bose
Rohan Bose
Founder, Analytics Firm
★★★★★
5.0

Robust restaurant extraction handles high volume; our swiggy apis pipeline is solid now.

Anita Reddy
Anita Reddy
DevOps Lead
★★★★★
5.0

Perfect for building restaurant datasets – fast, accurate extraction restaurant data saved us weeks of manual work.

Raj Patel
Raj Patel
Data Analyst
★★★★★
4.9

Swiggy apis integration was seamless; our restaurant crawler now powers real-time competitor tracking.

Priya Sharma
Priya Sharma
CTO, FoodTech Startup
★★★★★
4.8

High-quality restaurants dataset with JSON fields exactly as needed – restaurant extraction excellence.

Amit Kumar
Amit Kumar
Backend Developer
★★★★★
5.0

Generated massive restaurant datasets effortlessly; the restaurant crawler handles scale perfectly.

Neha Gupta
Neha Gupta
Market Researcher
★★★★★
4.7

Restaurant extraction API transformed our pricing analysis – reliable and dataset quality is top-notch.

Vikram Singh
Vikram Singh
Product Manager
★★★★★
4.9

Easy swiggy apis setup for restaurant datasets; fast scraping without any blocks.

Sonia Mehra
Sonia Mehra
Growth Hacker
★★★★★
5.0

Clean restaurant crawler data fueled our models – accurate extraction restaurant insights.

Karan Desai
Karan Desai
ML Engineer
★★★★★
4.8

Built comprehensive restaurants dataset for dashboards; integration was a breeze.

Lakshmi Rao
Lakshmi Rao
BI Analyst
★★★★★
4.9

Restaurant datasets from this scraper are gold – precise and scalable for clients.

Rohan Bose
Rohan Bose
Founder, Analytics Firm
★★★★★
5.0

Robust restaurant extraction handles high volume; our swiggy apis pipeline is solid now.

Anita Reddy
Anita Reddy
DevOps Lead
★★★★★
5.0

Perfect for building restaurant datasets – fast, accurate extraction restaurant data saved us weeks of manual work.

Raj Patel
Raj Patel
Data Analyst
★★★★★
4.9

Swiggy apis integration was seamless; our restaurant crawler now powers real-time competitor tracking.

Priya Sharma
Priya Sharma
CTO, FoodTech Startup
★★★★★
4.8

High-quality restaurants dataset with JSON fields exactly as needed – restaurant extraction excellence.

Amit Kumar
Amit Kumar
Backend Developer
★★★★★
5.0

Generated massive restaurant datasets effortlessly; the restaurant crawler handles scale perfectly.

Neha Gupta
Neha Gupta
Market Researcher
★★★★★
4.7

Restaurant extraction API transformed our pricing analysis – reliable and dataset quality is top-notch.

Vikram Singh
Vikram Singh
Product Manager
★★★★★
4.9

Easy swiggy apis setup for restaurant datasets; fast scraping without any blocks.

Sonia Mehra
Sonia Mehra
Growth Hacker
★★★★★
5.0

Clean restaurant crawler data fueled our models – accurate extraction restaurant insights.

Karan Desai
Karan Desai
ML Engineer
★★★★★
4.8

Built comprehensive restaurants dataset for dashboards; integration was a breeze.

Lakshmi Rao
Lakshmi Rao
BI Analyst
★★★★★
4.9

Restaurant datasets from this scraper are gold – precise and scalable for clients.

Rohan Bose
Rohan Bose
Founder, Analytics Firm
★★★★★
5.0

Robust restaurant extraction handles high volume; our swiggy apis pipeline is solid now.

Anita Reddy
Anita Reddy
DevOps Lead
★★★★★
5.0

Perfect for building restaurant datasets – fast, accurate extraction restaurant data saved us weeks of manual work.

Raj Patel
Raj Patel
Data Analyst
★★★★★
4.9

Swiggy apis integration was seamless; our restaurant crawler now powers real-time competitor tracking.

Priya Sharma
Priya Sharma
CTO, FoodTech Startup
★★★★★
4.8

High-quality restaurants dataset with JSON fields exactly as needed – restaurant extraction excellence.

Amit Kumar
Amit Kumar
Backend Developer
★★★★★
5.0

Generated massive restaurant datasets effortlessly; the restaurant crawler handles scale perfectly.

Neha Gupta
Neha Gupta
Market Researcher
★★★★★
4.7

Restaurant extraction API transformed our pricing analysis – reliable and dataset quality is top-notch.

Vikram Singh
Vikram Singh
Product Manager
★★★★★
4.9

Easy swiggy apis setup for restaurant datasets; fast scraping without any blocks.

Sonia Mehra
Sonia Mehra
Growth Hacker
★★★★★
5.0

Clean restaurant crawler data fueled our models – accurate extraction restaurant insights.

Karan Desai
Karan Desai
ML Engineer
★★★★★
4.8

Built comprehensive restaurants dataset for dashboards; integration was a breeze.

Lakshmi Rao
Lakshmi Rao
BI Analyst
★★★★★
4.9

Restaurant datasets from this scraper are gold – precise and scalable for clients.

Rohan Bose
Rohan Bose
Founder, Analytics Firm
★★★★★
5.0

Robust restaurant extraction handles high volume; our swiggy apis pipeline is solid now.

Anita Reddy
Anita Reddy
DevOps Lead
ISO 27001
XCrawlISO 27001
CDPR
XCrawlCDPR
Лучший по отзывам пользователей
XCrawlЛучший по отзывам пользователей
Лидер
XCrawlЛидер
Самый удобный
XCrawlСамый удобный
Лучшая выгода
XCrawlЛучшая выгода

Часто задаваемые вопросы

Всё, что нужно знать о XCrawl.

How does the Swiggy Dineout Restaurants Scraper API architecture work?
It uses distributed crawlers with proxy rotation to fetch, parse, and structure public Swiggy Dineout data into JSON via REST endpoints or dashboard.
What factors determine the pricing model?
Pricing scales with data volume, request frequency, and premium features like real-time streaming or custom restaurant datasets.
What is the data coverage and any limitations?
Full coverage of public Swiggy Dineout listings, menus, reviews; excludes private user data or dynamic login-protected content.
Is this legal and compliant for restaurant extraction?
We scrape only publicly available data, adhering to robots.txt and ToS where possible; users should verify for their restaurant datasets use.
What integration support is available?
SDKs for Python/Node.js, detailed docs, API playground, and Slack support for swift swiggy apis and restaurant crawler setup.

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