logo

Yatra Scraper - Scrape Yatra Flight, Hotel, and Holiday Data

RealdataAPI / yatra-scraper

Real Data API offers a powerful solution with its Yatra Scraper, enabling businesses to extract accurate flight, hotel, and holiday package data from the platform in real time. With advanced Yatra API data scraping, travel companies can track fare changes, monitor availability, and analyze competitor strategies across multiple destinations. This helps improve pricing decisions, demand forecasting, and customer targeting efforts. By leveraging a clean and structured Yatra Travel Dataset, organizations gain actionable insights that support smarter marketing campaigns, better inventory planning, and stronger revenue management. Whether you’re a travel agency, OTA, or analytics provider, Real Data API equips you with scalable travel intelligence for sustained competitive advantage.

What is Yatra Data Scraper, and How Does It Work?

A Yatra data scraper is a tool designed to automatically collect travel information such as flight schedules, hotel prices, and holiday packages from the platform. A Yatra travel data scraper works by scanning web pages or APIs to extract structured data like fares, availability, ratings, and discounts. This data is then organized into usable formats for analytics and reporting. Businesses rely on such tools to monitor market trends, compare competitor offerings, and improve strategic planning. Automated scraping removes the need for manual searches and ensures access to consistent, up-to-date travel insights.

Why Extract Data from Yatra?

Travel pricing and availability change rapidly, making real-time insights essential for staying competitive. When you Scrape Yatra flight, hotel, and holiday data, you gain instant visibility into fare trends, seasonal offers, and destination demand patterns. This information helps travel agencies and OTAs optimize pricing strategies, build better packages, and personalize customer experiences. Extracted data also supports demand forecasting and competitor benchmarking, allowing businesses to anticipate shifts in the market. By leveraging accurate travel intelligence, companies can enhance revenue management, improve customer targeting, and make data-driven decisions that strengthen long-term growth.

Is It Legal to Extract Yatra Data?

The legality of Yatra pricing data scraping depends on how data is collected and used. Scraping publicly available information for analysis, research, or competitive benchmarking is generally acceptable when done responsibly and in line with platform terms of service. However, excessive requests, misuse of proprietary content, or violation of data protection laws can create legal risks. Businesses should follow ethical scraping practices, respect robots.txt guidelines, and ensure compliance with applicable regulations. Partnering with professional data providers further reduces risk by ensuring that extraction methods remain secure, transparent, and aligned with industry standards.

How Can I Extract Data from Yatra?

There are multiple ways to gather travel insights, but automated tools offer the most efficient solution. A Yatra travel booking data extractor enables businesses to collect flight fares, hotel availability, and package details in real time. These tools use APIs, custom scripts, or third-party platforms to streamline data collection while minimizing errors. Once extracted, the data can be integrated into analytics dashboards, CRM systems, or pricing engines. This automation not only saves time but also improves accuracy, helping travel brands make faster, smarter decisions in a highly competitive market.

Do You Want More Yatra Scraping Alternatives?

Relying on a single data source can limit market visibility. Expanding beyond Yatra hotel and flight data extraction allows businesses to compare trends across multiple travel platforms and gain a broader understanding of customer behavior. Multi-source data strategies help identify pricing gaps, demand shifts, and regional travel preferences more accurately. By diversifying data inputs, travel brands strengthen forecasting models and improve promotional planning. Exploring alternative scraping options ensures better resilience in changing markets and supports long-term business growth through richer, more comprehensive travel intelligence.

Input options

Input options play a vital role in customizing how travel data is collected and analyzed. By setting filters such as origin, destination, travel dates, budget range, airline preference, hotel rating, and package type, businesses can retrieve only the most relevant information. With the Real-time Yatra travel data API, companies gain instant access to live flight fares, hotel availability, and holiday deals based on these inputs. This flexibility ensures faster decision-making for pricing strategies, promotions, and demand forecasting. Well-designed input options improve data accuracy, reduce processing time, and help travel brands respond quickly to changing market conditions.

Sample Result of Yatra Data Scraper

{
  "source": "Yatra",
  "scrape_date": "2026-01-11",
  "search_parameters": {
    "from": "DEL",
    "to": "BLR",
    "check_in": "2026-02-15",
    "check_out": "2026-02-18"
  },
  "flights": [
    {
      "airline": "Air India",
      "flight_number": "AI-812",
      "departure_time": "07:20",
      "arrival_time": "09:50",
      "price": 5320,
      "currency": "INR",
      "availability": "Available"
    },
    {
      "airline": "IndiGo",
      "flight_number": "6E-457",
      "departure_time": "13:45",
      "arrival_time": "16:15",
      "price": 4890,
      "currency": "INR",
      "availability": "Limited Seats"
    }
  ],
  "hotels": [
    {
      "hotel_name": "The Grand Bangalore",
      "location": "Bangalore",
      "rating": 4.5,
      "price_per_night": 4299,
      "currency": "INR",
      "room_type": "Deluxe",
      "availability": "Available"
    }
  ],
  "holiday_packages": [
    {
      "package_name": "Bangalore Weekend Getaway",
      "duration": "3 Days / 2 Nights",
      "price": 11999,
      "currency": "INR",
      "inclusions": ["Hotel Stay", "Breakfast", "City Tour"]
    }
  ]
}

Integrations with Yatra Scraper – Yatra Data Extraction

Integrating a Yatra Scraper with business systems allows seamless access to real-time travel intelligence. With automated workflows, companies can connect extracted data directly to analytics dashboards, pricing engines, and CRM platforms for faster decision-making. Tools that Extract Yatra listings and availability data provide instant visibility into flight seats, hotel rooms, and holiday packages across destinations. Additionally, a Yatra catalog scraper for travel market insights helps analyze trends, competitor pricing, and seasonal demand patterns. These integrations reduce manual effort, improve data accuracy, and empower travel brands to make smarter, faster decisions in revenue management, promotions, and customer engagement.

Executing Yatra Data Scraping with Real Data API

Executing Yatra data scraping with Real Data API allows travel businesses to access accurate, real-time intelligence efficiently. The Yatra Data Scraping API automates the collection of flight fares, hotel prices, and holiday package details, ensuring consistent and structured data for analysis. This enables companies to monitor market trends, track competitor pricing, and optimize revenue strategies. By leveraging a clean Yatra Travel Dataset, businesses can perform deeper analytics, forecast demand, and plan promotions more effectively. Automated scraping reduces manual effort, improves data reliability, and empowers travel brands to make faster, data-driven decisions that enhance operational efficiency and customer satisfaction.

You should have a Real Data API account to execute the program examples. Replace in the program using the token of your actor. Read about the live APIs with Real Data API docs for more explanation.

import { RealdataAPIClient } from 'RealDataAPI-client';

// Initialize the RealdataAPIClient with API token
const client = new RealdataAPIClient({
    token: '',
});

// Prepare actor input
const input = {
    "categoryOrProductUrls": [
        {
            "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
        }
    ],
    "maxItems": 100,
    "proxyConfiguration": {
        "useRealDataAPIProxy": true
    }
};

(async () => {
    // Run the actor and wait for it to finish
    const run = await client.actor("junglee/amazon-crawler").call(input);

    // Fetch and print actor results from the run's dataset (if any)
    console.log('Results from dataset');
    const { items } = await client.dataset(run.defaultDatasetId).listItems();
    items.forEach((item) => {
        console.dir(item);
    });
})();
from realdataapi_client import RealdataAPIClient

# Initialize the RealdataAPIClient with your API token
client = RealdataAPIClient("")

# Prepare the actor input
run_input = {
    "categoryOrProductUrls": [{ "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5" }],
    "maxItems": 100,
    "proxyConfiguration": { "useRealDataAPIProxy": True },
}

# Run the actor and wait for it to finish
run = client.actor("junglee/amazon-crawler").call(run_input=run_input)

# Fetch and print actor results from the run's dataset (if there are any)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
# Set API token
API_TOKEN=<YOUR_API_TOKEN>

# Prepare actor input
cat > input.json <<'EOF'
{
  "categoryOrProductUrls": [
    {
      "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
    }
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useRealDataAPIProxy": true
  }
}
EOF

# Run the actor
curl "https://api.realdataapi.com/v2/acts/junglee~amazon-crawler/runs?token=$API_TOKEN" \
  -X POST \
  -d @input.json \
  -H 'Content-Type: application/json'

Place the Amazon product URLs

productUrls Required Array

Put one or more URLs of products from Amazon you wish to extract.

Max reviews

Max reviews Optional Integer

Put the maximum count of reviews to scrape. If you want to scrape all reviews, keep them blank.

Link selector

linkSelector Optional String

A CSS selector saying which links on the page (< a> elements with href attribute) shall be followed and added to the request queue. To filter the links added to the queue, use the Pseudo-URLs and/or Glob patterns setting. If Link selector is empty, the page links are ignored. For details, see Link selector in README.

Mention personal data

includeGdprSensitive Optional Array

Personal information like name, ID, or profile pic that GDPR of European countries and other worldwide regulations protect. You must not extract personal information without legal reason.

Reviews sort

sort Optional String

Choose the criteria to scrape reviews. Here, use the default HELPFUL of Amazon.

Options:

RECENT,HELPFUL

Proxy configuration

proxyConfiguration Required Object

You can fix proxy groups from certain countries. Amazon displays products to deliver to your location based on your proxy. No need to worry if you find globally shipped products sufficient.

Extended output function

extendedOutputFunction Optional String

Enter the function that receives the JQuery handle as the argument and reflects the customized scraped data. You'll get this merged data as a default result.

{
  "categoryOrProductUrls": [
    {
      "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
    }
  ],
  "maxItems": 100,
  "detailedInformation": false,
  "useCaptchaSolver": false,
  "proxyConfiguration": {
    "useRealDataAPIProxy": true
  }
}
INQUIRE NOW