Free Proxy Chain
Stable Proxies:
IP address | Port | Country | Protocol | Verified |
---|---|---|---|---|
5.39.69.35 | 35956 | France | socks | 39 minute ago |
188.165.192.99 | 36188 | France | socks | 5 hours ago |
188.165.192.99 | 27432 | France | socks | 11 hours ago |
54.37.86.163 | 41712 | France | socks | 13 hours ago |
51.210.111.216 | 62160 | France | socks | 16 hours ago |
199.34.228.73 | 80 | United States | http | 19 hours ago |
51.210.111.216 | 16466 | France | socks | 20 hours ago |
51.210.111.216 | 33123 | France | socks | 21 hour ago |
51.75.121.63 | 12856 | France | socks | 21 hour ago |
162.19.107.54 | 50975 | France | socks | 21 hour ago |
116.202.48.78 | 50076 | Germany | socks | 23 hours ago |
162.19.107.54 | 34186 | France | socks | 1 day ago |
188.165.192.99 | 64004 | France | socks | 1 day ago |
162.19.107.54 | 54170 | France | socks | 1 day ago |
51.210.111.216 | 26732 | France | socks | 1 day ago |
51.158.148.158 | 3128 | France | http | 1 day ago |
193.124.67.4 | 1080 | Russian Federation | socks | 1 day ago |
51.75.126.150 | 58161 | France | socks | 1 day ago |
188.165.192.99 | 61700 | France | socks | 1 day ago |
95.216.174.12 | 50541 | Finland | socks | 1 day ago |
162.19.107.54 | 53114 | France | socks | 1 day ago |
46.105.124.216 | 44019 | United Kingdom | socks | 1 day ago |
85.214.223.203 | 31044 | Germany | socks | 1 day ago |
185.139.69.178 | 3128 | Russian Federation | http | 1 day ago |
5.39.69.35 | 64733 | France | socks | 2 day ago |
147.45.51.14 | 60932 | Italy | socks | 2 day ago |
79.137.197.141 | 3128 | Netherlands | http | 2 day ago |
95.216.174.12 | 29251 | Finland | socks | 2 day ago |
188.165.252.198 | 19446 | France | socks | 2 day ago |
46.105.105.223 | 29267 | United Kingdom | socks | 2 day ago |
85.175.219.236 | 1080 | Russian Federation | socks | 2 day ago |
31.220.184.161 | 8081 | Russian Federation | http | 2 day ago |
5.39.69.35 | 34248 | France | socks | 2 day ago |
5.39.69.35 | 35085 | France | socks | 2 day ago |
165.154.239.88 | 80 | Germany | http | 2 day ago |
85.118.117.165 | 8080 | Georgia | http | 2 day ago |
161.97.162.97 | 3129 | Germany | http | 2 day ago |
5.39.69.35 | 31427 | France | socks | 3 day ago |
188.165.192.99 | 57812 | France | socks | 3 day ago |
194.163.153.9 | 3128 | Germany | http | 3 day ago |
51.210.111.216 | 43311 | France | socks | 3 day ago |
5.39.69.35 | 63274 | France | socks | 3 day ago |
5.39.69.35 | 64363 | France | socks | 3 day ago |
51.75.126.150 | 33177 | France | socks | 3 day ago |
5.39.69.35 | 28311 | France | socks | 3 day ago |
85.214.223.203 | 39755 | Germany | socks | 3 day ago |
51.75.126.150 | 13960 | France | socks | 3 day ago |
5.39.69.35 | 53769 | France | socks | 3 day ago |
162.55.52.226 | 10006 | Germany | https | 3 day ago |
162.55.52.226 | 10003 | Germany | https | 3 day ago |
162.55.52.226 | 10005 | Germany | https | 3 day ago |
162.55.52.226 | 10009 | Germany | https | 3 day ago |
5.227.253.65 | 8424 | Russian Federation | http | 3 day ago |
188.165.192.99 | 63053 | France | socks | 3 day ago |
82.138.32.203 | 1080 | Russian Federation | socks | 3 day ago |
193.138.178.246 | 8282 | Russian Federation | http | 4 day ago |
65.21.24.174 | 37 | Finland | http | 4 day ago |
31.29.243.29 | 8424 | Russian Federation | http | 4 day ago |
172.64.69.24 | 80 | http | 4 day ago | |
172.67.170.75 | 80 | http | 4 day ago | |
188.114.98.235 | 80 | http | 4 day ago | |
95.216.174.12 | 31642 | Finland | socks | 4 day ago |
188.213.130.141 | 5555 | Switzerland | https | 4 day ago |
51.254.236.34 | 1443 | France | https | 4 day ago |
62.220.61.240 | 8424 | Russian Federation | http | 4 day ago |
213.147.201.84 | 7788 | Russian Federation | socks | 4 day ago |
165.227.140.18 | 40196 | Germany | socks | 4 day ago |
195.29.122.132 | 60606 | Croatia | socks | 5 days ago |
5.39.69.35 | 59136 | France | socks | 5 days ago |
176.97.122.225 | 5432 | Ukraine | http | 5 days ago |
176.97.122.213 | 5432 | Ukraine | http | 5 days ago |
185.196.68.106 | 3128 | Slovakia | https | 5 days ago |
31.29.245.6 | 8424 | Russian Federation | http | 5 days ago |
195.133.41.131 | 80 | United Kingdom | http | 5 days ago |
93.113.63.73 | 33100 | Turkey | http | 5 days ago |
185.32.124.132 | 35408 | Switzerland | http | 6 days ago |
185.123.101.160 | 80 | Turkey | http | 1 week ago |
46.0.205.8 | 1080 | Russian Federation | socks | 1 week ago |
5.227.255.153 | 8424 | Russian Federation | http | 1 week ago |
185.113.143.193 | 80 | Portugal | http | 1 week ago |
185.217.131.28 | 80 | Uzbekistan | http | 1 week ago |
5.189.130.42 | 23055 | Germany | http | 1 week ago |
91.107.187.245 | 8081 | Germany | socks | 1 week ago |
172.66.40.93 | 80 | Netherlands | http | 1 week ago |
172.67.69.65 | 80 | http | 1 week ago | |
172.67.68.15 | 80 | http | 1 week ago | |
172.64.147.209 | 80 | http | 1 week ago | |
172.67.40.130 | 80 | http | 1 week ago | |
172.66.41.36 | 80 | Netherlands | http | 1 week ago |
172.64.152.83 | 80 | Netherlands | http | 1 week ago |
172.67.74.220 | 80 | http | 1 week ago | |
172.67.73.153 | 80 | http | 1 week ago | |
172.67.224.13 | 80 | http | 1 week ago | |
51.75.126.150 | 15048 | France | socks | 1 week ago |
185.65.105.56 | 1080 | Netherlands | socks | 1 week ago |
188.165.192.99 | 57905 | France | socks | 1 week ago |
31.29.204.209 | 8424 | Russian Federation | http | 1 week ago |
51.75.126.150 | 45355 | France | socks | 1 week ago |
5.227.218.137 | 8424 | Russian Federation | http | 1 week ago |
82.117.212.234 | 5678 | Serbia | socks | 1 week 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 use web scraping to generate business leads?
Web scraping can be a useful way to generate business leads by extracting contact information from websites. Here are some steps you can follow to use web scraping to generate leads:
Identify the websites that contain the types of leads you are interested in. This may include business directories, industry-specific websites, or websites that list contact information for professionals or companies.
Use a web scraping tool or software to extract the data from the websites. There are many tools available that can automate the process of scraping data from websites, such as Import.io, ParseHub, or Web Scraper.
Set up the scraping tool to visit the specific pages on the websites and extract the data you are interested in. This may include contact names, email addresses, phone numbers, or other information. You may need to use different scraping techniques or methods depending on the structure of the websites and the data you want to scrape.
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.
Use the scraped data to generate leads by contacting the individuals or companies whose information you have collected. Be sure to follow best practices for generating leads, such as personalizing your communication and respecting the privacy of the individuals you are contacting.
It is important to be aware that web scraping may be against the terms of service of some websites, and it is a good idea to carefully review the terms of service of any website before attempting to scrape data from it.
What is a proxy error?
A proxy error is a message that indicates that a problem has occurred when trying to connect to a proxy server. There are several different types of proxy errors that can occur, each with its own cause and solution. Some common examples include:
1. "504 Gateway Timeout" error: This error occurs when the proxy server takes too long to receive a response from the target server. This could be due to the target server being down or the network connection being slow.
2. "403 Forbidden" error: This error occurs when the proxy server is not allowed to access the requested resource, usually because of an authentication issue.
3. "404 Not Found" error: This error occurs when the proxy server cannot find the requested resource on the target server.
4. "407 Proxy Authentication Required" error: This error occurs when the proxy server requires authentication to access the requested resource.
5. "500 Internal Server Error" error: This error occurs when there is a problem with the proxy server itself, such as a misconfiguration or a software issue.
If you encounter a proxy error, the first step is to try the request again later, as the issue may be temporary. If the error persists, you can try to resolve the issue by checking the configuration of the proxy server, clearing your browser's cache and cookies, or contacting the proxy server administrator for assistance.
What are the types of retail competitive pricing?
There are several types of competitive pricing strategies used in retail, including:
1. Price skimming: This strategy involves setting a high initial price for a new product and gradually lowering it over time as the product becomes more widely available and competitors enter the market.
2. Price matching: This strategy involves matching the prices of competitors in order to remain competitive and attract price-sensitive customers. Retailers who use this strategy may offer to match the prices of competitors in-store or online.
3. Price penetration: This strategy involves setting a low initial price for a product in order to quickly gain market share. The price may be increased later as the product becomes more established.
4. Price bundling: This strategy involves selling two or more products as a bundle at a discounted price. The goal is to encourage customers to purchase more products and increase overall sales.
5. Premium pricing: This strategy involves setting a higher price for a product in order to position it as a premium brand and differentiate it from competitors. Retailers who use this strategy often focus on providing high-quality products and excellent customer service.
6. Dynamic pricing: This strategy involves adjusting prices in real-time based on demand, supply, and other market conditions. For example, a retailer may use dynamic pricing to increase prices during periods of high demand and lower prices during periods of low demand.
It's important to note that these are general categories and that many retail businesses use a combination of these strategies in order to remain competitive and attract customers. The right pricing strategy will depend on the specific products and services offered, the target market, and the overall goals of the business.
What Is Fetch in Node.js?
fetch is an API in Node.js that allows you to make HTTP requests. It provides a simple and efficient way to make requests and retrieve data from web servers, APIs, and other web resources.
fetch is similar to the XMLHttpRequest API, but it is easier to use and provides a more modern API for making network requests. Unlike XMLHttpRequest, which requires a lot of code to set up and handle responses, fetch can be used with just a few lines of code.
Here's an example of using fetch to make a simple GET request in Node.js:
fetch('https://example.com/api/data')
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error(error));
In this example, the fetch function is used to make a GET request to the URL https://example.com/api/data. The response from the server is then converted to JSON using the json method and logged to the console. If there is an error during the request, it will be caught and logged to the console using the catch method.
The fetch API is supported in modern browsers and can also be used in Node.js using a polyfill library like node-fetch.
Where Is Web Crawling Used?
Web crawling is used in a variety of applications and industries. Some of the most common uses include:
1. Search engines: Web crawling is used by search engines like Google, Bing, and Yahoo! to index websites and build up a comprehensive database of the internet. This helps users find relevant information quickly and easily.
2. Price comparison: Online shopping websites use web crawling to gather information about products, prices, and availability from a variety of different e-commerce sites.
3. Market research: Companies use web crawling to collect data on their competitors, track industry trends, and gather information on consumer behavior.
4. Social media monitoring: Web crawling can be used to collect data from social media platforms like Twitter, Facebook, and Instagram to monitor brand mentions, sentiment, and user behavior.
5. Data mining: Web crawling is also used for data mining, which involves collecting and analyzing large amounts of data to uncover patterns and insights.
These are just a few examples of how web crawling is used. Overall, web crawling is a valuable tool for organizations that need to gather and process large amounts of data from the internet.
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