Expedia Hotel Data Aggregator - Organize and Examine Insights avatar
Expedia Hotel Data Aggregator - Organize and Examine Insights
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Expedia Hotel Data Aggregator - Organize and Examine Insights

Expedia Hotel Data Aggregator - Organize and Examine Insights

dainty_screw/expedia-hotel-collector---store-and-analyze-data
Try for free

14 days trial then $4.99/month - No credit card required now

Effortlessly gather and store key details of Expedia hotels, including names, ratings, and prices. Use our tool for competitive analysis and strategic planning in the hospitality sector.

The code examples below show how to run the Actor and get its results. To run the code, you need to have an Apify account. Replace <YOUR_API_TOKEN> in the code with your API token, which you can find under Settings > Integrations in Apify Console. Learn mode

Node.js

Python

curl

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4client = ApifyClient("<YOUR_API_TOKEN>")
5
6# Prepare the Actor input
7run_input = { "startUrls": [
8        {
9            "url": "https://www.expedia.com/Prague-Hotels-Hotel-Krystal.h10966026.Hotel-Information",
10            "method": "GET",
11            "userData": {
12                "hotel": "Prague Hotel Krystal",
13                "doWeEndorseIt": "no opinion",
14            },
15        },
16        {
17            "url": "https://www.expedia.it/en/Berchtesgaden-Hotels-Alpensport-Hotel-Seimler.h2692552.Hotel-Information",
18            "method": "GET",
19            "userData": {
20                "your": [
21                    "custom",
22                    "data",
23                    "goes",
24                    "here",
25                ],
26                "doWeEndorseThisHotel": "no opinion",
27            },
28        },
29    ] }
30
31# Run the Actor and wait for it to finish
32run = client.actor("dainty_screw/expedia-hotel-collector---store-and-analyze-data").call(run_input=run_input)
33
34# Fetch and print Actor results from the run's dataset (if there are any)
35for item in client.dataset(run["defaultDatasetId"]).iterate_items():
36    print(item)
Developer
Maintained by Community
Actor metrics
  • 3 monthly users
  • 96.2% runs succeeded
  • 0.0 days response time
  • Created in Apr 2024
  • Modified 10 days ago