Free Proxy 8080 port
Stable Proxies:
IP address | Port | Country | Protocol | Verified |
---|---|---|---|---|
213.219.198.69 | 80 | Russian Federation | http | 7 hours ago |
81.19.137.61 | 80 | France | socks | 8 hours ago |
193.233.232.116 | 80 | Austria | socks | 8 hours ago |
172.104.143.136 | 80 | Germany | http | 10 hours ago |
78.30.191.213 | 8080 | Serbia | http | 19 hours ago |
109.202.160.2 | 8888 | Russian Federation | http | 19 hours ago |
13.51.234.32 | 8096 | Sweden | http | 22 hours ago |
172.64.154.143 | 80 | United States | http | 1 day ago |
62.109.0.18 | 24101 | Russian Federation | socks | 1 day ago |
65.21.159.49 | 80 | Finland | http | 1 day ago |
77.232.128.191 | 80 | Russian Federation | http | 2 day ago |
46.105.44.110 | 80 | France | http | 2 day ago |
152.53.3.82 | 7891 | Austria | socks | 2 day ago |
152.53.3.82 | 7890 | Austria | https | 2 day ago |
172.64.144.179 | 80 | Netherlands | http | 2 day ago |
213.21.59.134 | 4153 | Russian Federation | socks | 2 day ago |
95.220.110.1 | 80 | Russian Federation | socks | 2 day ago |
93.177.67.178 | 80 | Germany | http | 3 day ago |
93.171.103.125 | 8080 | Russian Federation | http | 3 day ago |
104.244.76.38 | 80 | Luxembourg | http | 3 day ago |
34.175.101.255 | 80 | Spain | http | 3 day ago |
91.65.102.12 | 80 | Germany | http | 3 day ago |
178.252.170.222 | 3128 | Iran | http | 4 day ago |
195.231.69.203 | 80 | Italy | http | 4 day ago |
172.67.75.35 | 80 | United States | http | 4 day ago |
172.67.128.150 | 80 | United States | http | 4 day ago |
172.66.40.144 | 80 | United States | http | 4 day ago |
172.64.145.59 | 80 | United States | http | 4 day ago |
172.67.165.123 | 80 | United States | http | 4 day ago |
172.67.162.240 | 80 | United States | http | 4 day ago |
79.121.102.227 | 8080 | Hungary | http | 4 day ago |
37.140.31.63 | 80 | Russian Federation | http | 4 day ago |
159.69.206.198 | 80 | Germany | http | 4 day ago |
185.146.173.59 | 80 | Sweden | http | 4 day ago |
103.130.145.169 | 80 | Turkey | http | 4 day ago |
79.174.12.190 | 80 | Russian Federation | http | 5 days ago |
41.65.236.53 | 1976 | Egypt | http | 5 days ago |
172.64.145.223 | 80 | United States | http | 5 days ago |
91.148.127.60 | 8080 | Serbia | http | 5 days ago |
178.254.42.248 | 80 | Germany | http | 5 days ago |
172.67.182.221 | 80 | United States | http | 5 days ago |
172.67.68.245 | 80 | Netherlands | http | 5 days ago |
172.64.194.218 | 80 | United States | http | 5 days ago |
45.81.232.17 | 8191 | Germany | socks | 6 days ago |
66.235.200.122 | 80 | United States | http | 6 days ago |
172.67.163.136 | 80 | United States | http | 6 days ago |
77.221.136.210 | 80 | Sweden | http | 6 days 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 | 1 week ago |
213.91.232.94 | 8080 | Bulgaria | http | 1 week ago |
109.197.153.25 | 8888 | Russian Federation | http | 1 week ago |
178.48.68.61 | 18080 | Hungary | http | 1 week ago |
88.198.82.189 | 3128 | Germany | https | 1 week ago |
51.75.126.150 | 50677 | France | socks | 1 week ago |
185.221.160.17 | 80 | Russian Federation | http | 1 week ago |
89.179.112.252 | 5678 | Russian Federation | socks | 1 week ago |
51.75.126.150 | 48751 | France | socks | 1 week ago |
172.64.145.201 | 80 | United States | http | 1 week ago |
172.64.144.116 | 80 | United States | http | 1 week ago |
45.81.232.17 | 57668 | Germany | socks | 1 week ago |
45.81.232.17 | 37348 | Germany | socks | 1 week ago |
194.163.183.151 | 8899 | Germany | http | 1 week ago |
83.166.240.61 | 3031 | Russian Federation | https | 1 week ago |
45.81.232.17 | 25519 | Germany | socks | 1 week ago |
5.189.130.215 | 32293 | Germany | socks | 1 week ago |
5.189.130.215 | 32628 | Germany | socks | 1 week ago |
88.99.138.21 | 5801 | Germany | socks | 1 week ago |
45.153.230.46 | 80 | Germany | http | 1 week ago |
5.189.130.215 | 31224 | Germany | socks | 1 week ago |
45.81.232.17 | 54248 | Germany | socks | 1 week ago |
45.143.220.99 | 8118 | Netherlands | https | 1 week ago |
172.64.147.188 | 80 | United States | http | 2 weeks ago |
212.127.78.79 | 39811 | Poland | http | 2 weeks ago |
194.26.229.46 | 20004 | Russian Federation | socks | 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
|
Canada |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
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
|
France |
100 IP
19$
|
500 IP
69$
|
1 000 IP
99$
|
3 000 IP
Sold out
|
5 000 IP
Sold out
|
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 Scopus Journal?
Scopus is a database of academic journals, articles, and conference proceedings. If you want to scrape data from Scopus, there are a few steps you can follow:
1. Identify the specific data you want to scrape from Scopus. This may include article titles, authors, abstracts, or other details about the articles.
2. Determine the specific articles or journals on Scopus 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 Scopus 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 Scopus and extract the data you are interested in. You may need to use different scraping techniques or methods depending on the structure of the Scopus 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 Scopus. It is a good idea to carefully review the terms of service of any website before attempting to scrape data from it.
What are the best proxies for Enterprises?
The best proxies for enterprises depend on the specific needs and requirements of the enterprise. Some factors to consider when choosing a proxy for an enterprise include:
Speed: Look for a proxy with fast connection speeds, as slow proxy speeds can affect the performance of the enterprise's tools and services.
Reliability: Choose a proxy service that has a good reputation for reliability and uptime.
Compatibility: Make sure the proxy is compatible with the enterprise's tools and services.
Location: Consider the location of the proxy server and whether it will allow the enterprise to access the specific websites or data that it needs.
Security and anonymity: Look for a proxy that offers good security and anonymity protection, such as encryption and the ability to hide the enterprise's IP addresses.
Scalability: Choose a proxy service that can handle the enterprise's needs as it grows and scales.
Customer support: Look for a proxy service with good customer support and resources, such as a knowledge base or online tutorials.
Some popular proxy services that may be suitable for enterprises include Luminati, StormProxies, and PapaProxy. However, it is important to carefully research any proxy service before using it, and to consider the specific needs and requirements of the enterprise.
How to scrape YouTube with Web Scraping API?
To scrape YouTube with a web scraping API, you will need to find a suitable API provider and sign up for an API key. Once you have the API key, you can start making API requests to extract data from YouTube.
Here's a high-level overview of how the process works:
1. Identify the data you want to scrape from YouTube. This might include information such as video titles, descriptions, uploader names, views, and more.
2. Determine the API endpoint that corresponds to the data you want to scrape. Most web scraping APIs provide a list of endpoints for different types of data.
3. Make API requests to the endpoint using the API key. The API request should include parameters such as the YouTube channel ID, video ID, or search query, depending on the data you want to extract.
4. Receive the API response in a structured format, such as JSON or XML. The API response will contain the requested data, which you can then process and extract as needed.
5. Store the extracted data in a database, file, or another format for future use.
It's important to note that web scraping APIs are subject to rate limiting and other restrictions, so be sure to review the API provider's terms of use before using the API for web scraping purposes. Additionally, some web scraping APIs may not provide access to all the data you need, so you may need to supplement the API with other scraping techniques.
How to nail web scraping?
Here are some tips to help you nail web scraping:
Know the website's terms of use: Before you start scraping, make sure you understand the website's terms of use and that web scraping is allowed. Some websites explicitly prohibit web scraping.
Use a headless browser: If you need to interact with a website dynamically, consider using a headless browser, such as Puppeteer or Selenium, to automate browser actions.
Use a well-designed scraping framework: Consider using a well-designed scraping framework, such as Scrapy or BeautifulSoup, to simplify your scraping code and make it more efficient.
Handle errors gracefully: Web scraping can be unpredictable, so make sure your code is able to handle errors gracefully and can continue running even if part of the scraping process fails.
Cache data: Consider caching the data you scrape to reduce the number of requests you make to the website and to speed up subsequent scraping runs.
Throttle requests: Make sure to throttle your requests to the website to avoid overloading the server and to reduce the risk of your IP being banned.
Store data efficiently: Store the data you scrape efficiently to reduce the memory footprint of your scraping process and to make it easier to analyze and manipulate the data later.
By following these tips, you can help ensure that your web scraping is effective and efficient.
What is an XPath selector?
XPath (XML Path Language) is a language used for navigating and selecting elements within an XML document. In the context of web scraping, XPath selectors are used to select elements within an HTML document.
An XPath selector is a string of text that defines a specific path to an element within an HTML document. For example, an XPath selector could be used to select the title of an article on a website, the links within a navigation menu, or the text within a specific section of the page.
XPath selectors can be used in combination with web scraping libraries, such as BeautifulSoup in Python, to extract data from websites. XPath selectors allow developers to precisely select the elements they want to extract, making them a powerful tool for web scraping.
To create an XPath selector, you need to have a basic understanding of the structure of an HTML document and the elements it contains. There are many tools available for creating XPath selectors, such as browser plugins and online XPath builder tools, that can help simplify the process.
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