(Image source: TravelFares official website)
Using Rotating Residential Proxies for travel price comparison business can improve data capture efficiency and personal data protection. Combine travel price comparison to compare prices, search and plan trips on the TravelFares website. Read this article to get 600MB free traffic to residential proxies, return here and click residential proxy to buy, you can also get internal discount.
What is TravelFares
(Image source: TravelFares official website)
TravelFares is a travel price comparison website that provides a search and comparison service for flights, hotels and vacation packages. Users can find prices from different airlines and travel proxies on the site to help them find the best travel options and deals. The site provides destination information, travel advice and related services and aims to provide travelers with a convenient travel planning experience.
1. Choose the right residential proxies service
Choose a reliable residential proxies provider such as NaProxy to ensure it has high anonymity and stable connections.
2. Set up target websites
Determine the travel comparison products to be crawled, such as TravelFares, which is a comparison platform for flights, hotels, and so on.
3. Configure the crawling tool
Use a web crawler or write a script to access the target website via residential proxies to avoid being blocked due to frequent requests.
Taking https://travelfares.co.uk/ as an example, here is a simple Python crawling code example that
Crawling https://travelfares.co.uk/ using requests and BeautifulSoup library.
import requestsfrom bs4 import BeautifulSoup
# Set up the proxies
proxies = {
“http": ‘http://your_residential_proxy_ip:port’,
“https": ‘http://your_residential_proxy_ip:port’,
}
# Destination URL
url = “https://travelfares.co.uk/”
# Send the request
response = requests.get(url, proxies=proxies)
# Check if the request was successful if response.status_code == 200.
# Parse the HTML content
soup = BeautifulSoup(response.text, 'html.parser')
# Example: grabbing the title
title = soup.find('title').text
print(f “Page title: {title}”)
# Example: Grabbing flight information (adjusted to the actual HTML structure)
flight_info = soup.find_all('div', class_='flight-info-class') # change to actual class
for flight in flight_info.
print(flight.text.strip())else.
print(f “Request failed, status code: {response.status_code}”)
Notes
1. Proxy settings: replace your_residential_proxy_ip and port with actual proxies.
2. Crawl frequency: control the request frequency to avoid being banned.
3. Follow robots.txt: Check the robots.txt file of the target website to make sure the crawling behavior is in line with its regulations.
4. Optimize request frequency
The purpose of optimizing the request frequency is to reduce the risk of being blocked by the target website, the following are some effective methods:
1. Setting delays
Add a random delay between each request, usually using the `time.sleep()` function, the delay can be randomly selected between 1 and 5 seconds.
2. Use a polling strategy
Rotate multiple proxies so that each one handles a certain number of requests and then switches to the next one, reducing the amount of requests from a single proxy.
3. Limit the number of requests
Control the request frequency to avoid triggering anti-crawler.
Set the maximum number of requests for each crawl to avoid sending a large number of requests in a short period of time.
4. Simulate user behavior
Simulate user browsing behavior by adding random mouse movements, clicks and other actions, which can be achieved by using automation tools (e.g. Selenium).
5. Monitoring status code
Regularly check the response status code, if it returns 429 (too many requests) or 403 (forbidden access), then increase the delay or pause the crawl.
6. Using Proxy Pools
Use proxy pool to manage multiple IP addresses and dynamically select proxies for requests to reduce the frequency of requests from the same IP.
7. Randomize the order of requests
Randomize the order of the target page of the request to avoid visiting the same page too often.
8. Configure retry mechanism
Configure the retry mechanism when the request fails to avoid request failure due to temporary network problems.
5. Analyzing data
Collect and organize the captured data for price comparison, trend analysis, etc.
6. Keep Updating
Regularly update the data crawling strategy to cope with the changes and updates of the target websites.
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