Hiload.org Free Proxy
Stable Proxies:
IP address | Port | Country | Protocol | Verified |
---|---|---|---|---|
172.67.72.188 | 80 | United States | http | 1 hour ago |
194.26.229.46 | 20002 | Russian Federation | socks | 1 day ago |
194.26.229.46 | 20009 | Russian Federation | socks | 1 day ago |
161.123.116.54 | 22332 | Canada | http | 1 day ago |
37.186.66.36 | 3629 | Armenia | socks | 1 day ago |
85.21.233.231 | 1337 | Russian Federation | socks | 1 day ago |
172.67.160.84 | 80 | United States | http | 1 day ago |
172.67.165.174 | 80 | United States | http | 1 day ago |
172.66.0.96 | 80 | United States | http | 1 day ago |
91.107.143.161 | 3128 | Germany | http | 2 day ago |
91.201.119.198 | 1337 | Russian Federation | socks | 2 day ago |
89.133.137.45 | 4145 | Hungary | socks | 2 day ago |
77.68.77.181 | 80 | United Kingdom | http | 2 day ago |
92.205.110.118 | 35153 | France | socks | 2 day ago |
83.17.171.252 | 36099 | Poland | socks | 3 day ago |
173.212.223.23 | 28083 | Germany | socks | 3 day ago |
213.219.198.69 | 80 | Russian Federation | http | 3 day ago |
81.19.137.61 | 80 | France | socks | 3 day ago |
193.233.232.116 | 80 | Austria | socks | 3 day ago |
172.104.143.136 | 80 | Germany | http | 3 day ago |
78.30.191.213 | 8080 | Serbia | http | 4 day ago |
109.202.160.2 | 8888 | Russian Federation | http | 4 day ago |
13.51.234.32 | 8096 | Sweden | http | 4 day ago |
172.64.154.143 | 80 | United States | http | 4 day ago |
62.109.0.18 | 24101 | Russian Federation | socks | 5 days ago |
65.21.159.49 | 80 | Finland | http | 5 days ago |
77.232.128.191 | 80 | Russian Federation | http | 5 days ago |
46.105.44.110 | 80 | France | http | 5 days ago |
152.53.3.82 | 7891 | Austria | socks | 5 days ago |
152.53.3.82 | 7890 | Austria | https | 5 days ago |
172.64.144.179 | 80 | Netherlands | http | 5 days ago |
213.21.59.134 | 4153 | Russian Federation | socks | 5 days ago |
95.220.110.1 | 80 | Russian Federation | socks | 6 days ago |
93.177.67.178 | 80 | Germany | http | 6 days ago |
93.171.103.125 | 8080 | Russian Federation | http | 6 days ago |
104.244.76.38 | 80 | Luxembourg | http | 6 days ago |
34.175.101.255 | 80 | Spain | http | 6 days ago |
91.65.102.12 | 80 | Germany | http | 1 week ago |
178.252.170.222 | 3128 | Iran | http | 1 week ago |
195.231.69.203 | 80 | Italy | http | 1 week ago |
172.67.75.35 | 80 | United States | http | 1 week ago |
172.67.128.150 | 80 | United States | http | 1 week ago |
172.66.40.144 | 80 | United States | http | 1 week ago |
172.64.145.59 | 80 | United States | http | 1 week ago |
172.67.165.123 | 80 | United States | http | 1 week ago |
172.67.162.240 | 80 | United States | http | 1 week ago |
79.121.102.227 | 8080 | Hungary | http | 1 week ago |
37.140.31.63 | 80 | Russian Federation | http | 1 week ago |
159.69.206.198 | 80 | Germany | http | 1 week ago |
185.146.173.59 | 80 | Sweden | http | 1 week ago |
103.130.145.169 | 80 | Turkey | http | 1 week ago |
79.174.12.190 | 80 | Russian Federation | http | 1 week ago |
41.65.236.53 | 1976 | Egypt | http | 1 week ago |
172.64.145.223 | 80 | United States | http | 1 week ago |
91.148.127.60 | 8080 | Serbia | http | 1 week ago |
178.254.42.248 | 80 | Germany | http | 1 week ago |
172.67.182.221 | 80 | United States | http | 1 week ago |
172.67.68.245 | 80 | Netherlands | http | 1 week ago |
172.64.194.218 | 80 | United States | http | 1 week ago |
45.81.232.17 | 8191 | Germany | socks | 1 week ago |
66.235.200.122 | 80 | United States | http | 1 week ago |
172.67.163.136 | 80 | United States | http | 1 week ago |
77.221.136.210 | 80 | Sweden | http | 1 week ago |
79.124.77.148 | 3128 | Bulgaria | http | 1 week ago |
176.10.111.23 | 80 | Switzerland | http | 1 week ago |
185.244.210.185 | 80 | France | http | 1 week ago |
95.110.227.85 | 3128 | Italy | http | 1 week ago |
147.45.104.252 | 80 | Russian Federation | http | 1 week ago |
206.189.12.206 | 80 | Netherlands | http | 1 week ago |
77.221.140.172 | 5556 | Sweden | socks | 1 week ago |
89.109.53.26 | 8123 | Russian Federation | http | 1 week ago |
217.160.99.39 | 80 | Germany | http | 1 week ago |
172.67.146.14 | 80 | United States | http | 1 week ago |
45.81.232.17 | 25306 | Germany | socks | 1 week ago |
91.228.186.61 | 80 | Turkey | http | 1 week ago |
45.81.232.17 | 22235 | Germany | socks | 1 week ago |
45.159.248.66 | 80 | United Kingdom | http | 1 week ago |
172.67.148.149 | 80 | United States | http | 1 week ago |
172.67.156.239 | 80 | United States | http | 1 week ago |
104.234.1.25 | 80 | Netherlands | http | 1 week ago |
91.107.142.189 | 80 | Germany | http | 1 week ago |
94.154.221.91 | 5678 | Ukraine | socks | 1 week ago |
46.164.227.196 | 1080 | Russian Federation | socks | 1 week ago |
45.81.232.17 | 63186 | Germany | socks | 1 week ago |
95.164.116.124 | 80 | Turkey | http | 1 week ago |
135.125.248.252 | 80 | Germany | http | 1 week ago |
88.198.161.3 | 80 | Germany | http | 1 week ago |
5.39.69.35 | 57486 | France | socks | 1 week ago |
185.105.118.72 | 80 | Finland | https | 1 week ago |
46.164.226.252 | 1080 | Russian Federation | socks | 1 week ago |
94.140.224.134 | 65056 | Russian Federation | https | 2 weeks ago |
213.91.232.94 | 8080 | Bulgaria | http | 2 weeks ago |
109.197.153.25 | 8888 | Russian Federation | http | 2 weeks ago |
178.48.68.61 | 18080 | Hungary | http | 2 weeks ago |
88.198.82.189 | 3128 | Germany | https | 2 weeks ago |
51.75.126.150 | 50677 | France | socks | 2 weeks ago |
185.221.160.17 | 80 | Russian Federation | http | 2 weeks ago |
89.179.112.252 | 5678 | Russian Federation | socks | 2 weeks ago |
51.75.126.150 | 48751 | France | socks | 2 weeks ago |
172.64.145.201 | 80 | United States | http | 2 weeks ago |
Fast and stable proxies
Russia |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
249$
|
5 000 IP
399$
|
USA |
100 IP
25$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
249$
|
5 000 IP
399$
|
Great Britain |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
249$
|
5 000 IP
399$
|
Germany |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
249$
|
5 000 IP
499$
|
Europe |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
229$
|
5 000 IP
379$
|
China |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
249$
|
5 000 IP
Sold out
|
Ukraine |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
Australia |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
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Canada |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
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5 000 IP
Sold out
|
Netherlands |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
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France |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
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Turkey |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
India |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
Poland |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
Spain |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
Mix of countries |
1 000 IP
99$
|
3 000 IP
229$
|
5 000 IP
379$
|
10 000 IP
729$
|
15 000 IP
1049$
|
FAQ
How to scrape data from Agoda?
Agoda is a website that provides online booking and reservation services for hotels and other accommodation. If you want to scrape data from Agoda, there are a few steps you can follow:
1. Identify the specific data you want to scrape from Agoda. This may include hotel names, prices, ratings, or other details about the hotels.
2. Determine the specific hotels or categories on Agoda that contain the data you want to scrape. You may need to use search filters or browse through multiple pages to find the relevant data.
3. Use a web scraping tool or software to extract the data from the Agoda website. There are many tools available that can automate the process of scraping data from websites, such as Import.io, ParseHub, or Web Scraper.
4. Set up the scraping tool to visit the specific pages on Agoda and extract the data you are interested in. You may need to use different scraping techniques or methods depending on the structure of the Agoda website and the data you want to scrape.
5. Save the scraped data in a format that is convenient for you to use or analyze. This could be a spreadsheet, database, or other format.
It is important to be aware that web scraping may be against the terms of service of some websites, including Agoda. It is a good idea to carefully review the terms of service of any website before attempting to scrape data from it.
Is it legal to scrape Twitter?
The legality of scraping Twitter depends on the specific circumstances and the specific information you are trying to extract. In general, it is not illegal to scrape public data from a website, but there are some conditions and restrictions that you need to be aware of.
Twitter has specific policies regarding the use of its data and APIs. You are allowed to scrape public data from Twitter, such as tweets, but you must adhere to the Twitter Developer Agreement and Policy. This policy outlines the restrictions on the use of Twitter data, including scraping, and requires that you follow best practices for data usage, such as rate limits and attribution.
Additionally, you cannot use Twitter data for spamming or other malicious purposes, and you must comply with the law and all relevant data protection and privacy regulations.
In summary, it is possible to scrape Twitter data, but you must follow the Twitter Developer Agreement and Policy and adhere to all relevant laws and regulations.
What are shopping bots?
Shopping bots are automated programs that are designed to perform online shopping tasks, such as price comparison, product search, and checkout. These bots simulate the actions of a human shopper, such as browsing websites, adding items to a shopping cart, and entering payment and shipping information.
Shopping bots are often used by consumers to save time and effort when shopping online, as well as by businesses for price monitoring and market research purposes. Some shopping bots can also be programmed to purchase limited-edition items, such as sneakers or concert tickets, as soon as they become available, increasing the chances of getting the item before it sells out.
There are different types of shopping bots, ranging from simple browser extensions to complex software systems. Some of the most popular shopping bots include Honey, Ibotta, and RetailMeNot.
However, the use of shopping bots can raise ethical and legal concerns, such as website scraping, copyright infringement, and artificial price inflation. Additionally, many online retailers have implemented measures to detect and prevent the use of shopping bots, such as using captchas or limiting the number of purchases per customer.
What headless browser should you choose?
The choice of headless browser depends on your specific needs and requirements. Some popular headless browsers include:
1. Puppeteer: Puppeteer is a Node.js library maintained by Google that provides a high-level API for controlling headless Chrome or Chromium browsers. It supports a wide range of testing and web scraping tasks, and provides a rich set of features for testing and automating web applications.
2. PhantomJS: PhantomJS is a headless browser that uses the WebKit rendering engine and JavaScriptCore. It supports a wide range of testing and automation tasks, and provides a simple and easy-to-use API for controlling the browser.
3. Selenium WebDriver: Selenium WebDriver is a browser automation framework that supports a wide range of headless browsers, including Chrome, Firefox, and Safari. It provides a flexible and powerful API for controlling the browser and automating web applications, and supports multiple programming languages, including Java, C#, and Python.
4. HtmlUnit: HtmlUnit is a headless browser that uses the Java programming language and provides a simple and easy-to-use API for controlling the browser. It supports JavaScript and is often used for web scraping and web testing tasks.
When choosing a headless browser, you should consider factors such as performance, compatibility with the websites you need to test, support for mouse and keyboard interactions, support for JavaScript, and the ease of use and accessibility of the API. You should also consider the level of community support and resources available for the specific tool you choose.
Scraping local product data from Amazon with location-targeted residential proxies
Scraping local product data from Amazon with location-targeted residential proxies can provide more accurate and localized information about product prices, customer reviews, and other market data. By using residential proxies that are located in the target geographical region, you can bypass Amazon's geolocation restrictions and access data that is specific to that region.
However, as with any type of web scraping, it's important to be aware of the legal implications and to ensure that you are not violating Amazon's terms of service. Scraping large amounts of data from the site without permission is not only unethical but can also result in legal consequences.
It's also important to choose a reliable and ethical proxy service provider that takes measures to protect your privacy and security while scraping. When using location-targeted residential proxies, it's important to regularly change your proxies to avoid detection and to ensure that your scraping activities are not disrupted.
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