Proxyscrape.com free proxy

Stable Proxies:

USA USA
100 IP
25$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
399$
Europe Europe
500 IP
69$
1 000 IP
99$
3 000 IP
229$
5 000 IP
379$
10 000 IP
729$
IP address Port Country Protocol Verified
88.202.230.103 7392 United Kingdom socks 12 hours ago
94.23.220.136 56714 France socks 22 hours ago
5.75.206.99 80 Germany http 22 hours ago
95.111.227.164 53152 Germany socks 1 day ago
195.35.29.39 80 Germany http 1 day ago
134.209.67.109 8086 United States http 1 day ago
5.228.229.33 80 Russian Federation http 1 day ago
84.247.128.92 3128 Germany http 1 day ago
51.89.73.162 80 United Kingdom http 1 day ago
185.196.178.152 4145 Austria socks 1 day ago
5.180.45.235 80 Cyprus http 1 day ago
65.21.49.83 8080 Finland http 1 day ago
51.210.19.141 80 France http 1 day ago
155.133.57.22 4153 Poland socks 2 day ago
178.208.10.237 1080 France socks 2 day ago
82.65.220.152 80 France http 2 day ago
173.212.237.43 27004 Germany socks 2 day ago
91.235.69.164 8382 Ukraine http 2 day ago
91.202.25.154 9090 Russian Federation http 2 day ago
164.92.167.4 1194 Germany http 2 day ago
156.200.116.72 1976 Egypt http 3 day ago
130.180.208.145 80 France http 3 day ago
185.152.113.67 9999 Slovakia http 4 day ago
217.65.2.14 3333 Russian Federation http 4 day ago
194.26.229.46 20000 Russian Federation socks 4 day ago
172.64.165.79 80 United States http 4 day ago
172.67.72.188 80 United States http 4 day ago
194.26.229.46 20002 Russian Federation socks 5 days ago
194.26.229.46 20009 Russian Federation socks 6 days ago
161.123.116.54 22332 Canada http 6 days ago
37.186.66.36 3629 Armenia socks 6 days ago
85.21.233.231 1337 Russian Federation socks 6 days ago
172.67.160.84 80 United States http 6 days ago
172.67.165.174 80 United States http 6 days ago
172.66.0.96 80 United States http 6 days ago
91.107.143.161 3128 Germany http 1 week ago
91.201.119.198 1337 Russian Federation socks 1 week ago
89.133.137.45 4145 Hungary socks 1 week ago
77.68.77.181 80 United Kingdom http 1 week ago
92.205.110.118 35153 France socks 1 week ago
83.17.171.252 36099 Poland socks 1 week ago
173.212.223.23 28083 Germany socks 1 week ago
213.219.198.69 80 Russian Federation http 1 week ago
81.19.137.61 80 France socks 1 week ago
193.233.232.116 80 Austria socks 1 week ago
172.104.143.136 80 Germany http 1 week ago
78.30.191.213 8080 Serbia http 1 week ago
109.202.160.2 8888 Russian Federation http 1 week ago
13.51.234.32 8096 Sweden http 1 week ago
172.64.154.143 80 United States http 1 week ago
62.109.0.18 24101 Russian Federation socks 1 week ago
65.21.159.49 80 Finland http 1 week ago
77.232.128.191 80 Russian Federation http 1 week ago
46.105.44.110 80 France http 1 week ago
152.53.3.82 7891 Austria socks 1 week ago
152.53.3.82 7890 Austria https 1 week ago
172.64.144.179 80 Netherlands http 1 week ago
213.21.59.134 4153 Russian Federation socks 1 week ago
95.220.110.1 80 Russian Federation socks 1 week ago
93.177.67.178 80 Germany http 1 week ago
93.171.103.125 8080 Russian Federation http 1 week ago
104.244.76.38 80 Luxembourg http 1 week ago
34.175.101.255 80 Spain http 1 week 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 2 weeks ago
66.235.200.122 80 United States http 2 weeks ago
172.67.163.136 80 United States http 2 weeks ago
77.221.136.210 80 Sweden http 2 weeks ago
79.124.77.148 3128 Bulgaria http 2 weeks ago
176.10.111.23 80 Switzerland http 2 weeks ago
185.244.210.185 80 France http 2 weeks ago
95.110.227.85 3128 Italy http 2 weeks ago
147.45.104.252 80 Russian Federation http 2 weeks ago
206.189.12.206 80 Netherlands http 2 weeks ago
77.221.140.172 5556 Sweden socks 2 weeks ago
89.109.53.26 8123 Russian Federation http 2 weeks ago
217.160.99.39 80 Germany http 2 weeks ago
172.67.146.14 80 United States http 2 weeks ago
45.81.232.17 25306 Germany socks 2 weeks ago

Fast and stable proxies

Russia Russia
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
399$
USA USA
100 IP
25$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
399$
Great Britain Great Britain
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
399$
Germany Germany
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
499$
Europe Europe
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
229$
5 000 IP
379$
China China
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
249$
5 000 IP
Sold out
Ukraine Ukraine
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Australia Australia
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Canada Canada
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Netherlands Netherlands
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
France France
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Turkey Turkey
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
India India
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Poland Poland
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Spain Spain
100 IP
19$
500 IP
69$
1 000 IP
99$
3 000 IP
Sold out
5 000 IP
Sold out
Mix of countriesMix of countries
1 000 IP
99$
3 000 IP
229$
5 000 IP
379$
10 000 IP
729$
15 000 IP
1049$
We have proxy lists for almost every need, the list is updated every 60 minutes. We analyze proxy every minute, look for speed matching IPs and add them to our database. You can see the result in the table above. Use our proxies and regularly check for updates on our website.

FAQ

    What are residential proxies and when you should use them?

    Residential proxies are proxy servers that use real IP addresses assigned to physical devices, such as computers or routers. They are often used to hide the IP address of the user and to bypass internet restrictions, such as blocking or filtering of websites.

    Residential proxies are generally more anonymous than datacenter proxies, as they use real IP addresses that are assigned to physical devices. They are also generally more expensive and less stable than datacenter proxies.

    Residential proxies are commonly used for tasks such as web scraping, online marketing, and search engine optimization (SEO). They are also often used to bypass geolocation restrictions and to access blocked websites or content.

    In summary, residential proxies are proxy servers that use real IP addresses assigned to physical devices. They are generally more anonymous than datacenter proxies, but are also generally more expensive and less stable. They are commonly used for tasks such as web scraping, online marketing, and SEO, and are also often used to bypass geolocation restrictions and access blocked websites or content.

    Why would you scrape Instagram followers’ emails?

    There are several reasons why someone might want to scrape the emails of Instagram followers:

    1. Marketing: Businesses and marketers can use email addresses to send targeted marketing campaigns to Instagram followers.
    2. Lead Generation: Email addresses can be used to generate leads for sales purposes. By scraping the emails of Instagram followers, businesses can reach out to potential customers directly and offer their products or services.
    3. Research: Researchers can use email addresses to conduct surveys or other types of research on Instagram users.
    4. Social Media Analytics: Email addresses can be used to analyze social media activity and understand the behavior of Instagram users.

    It's important to note that scraping emails from Instagram followers without their consent is illegal and unethical. It's always recommended to obtain permission before collecting and using someone's personal information, such as their email address.

    Ways to scrape YouTube comments?

    There are several ways to scrape comments from YouTube videos, including the following:

    1. YouTube API: You can use the YouTube API to retrieve comments from YouTube videos. However, you will need an API key and some programming skills to use the API.
    2. Web Scraping: You can scrape comments from YouTube videos by writing a script to extract the comments from the HTML source code of the video page. This requires some programming skills, but it is a flexible method that can be done in any programming language.
    3. Third-party tools: There are also third-party tools that can scrape comments from YouTube videos for you. Some of these tools are free and some are paid, and they often require little to no technical knowledge to use.

    Regardless of the method you choose, it is important to be aware of the terms of service for YouTube, which prohibit the use of automated means to scrape comments from the site. It is also important to respect users' privacy and only use this information for legitimate purposes.

    Why Scrape Instagram Followers?

    People or organizations might scrape Instagram followers for a variety of reasons. Some of the reasons for scraping Instagram followers include:

    1. Market research: Understanding the demographics and interests of a target audience can help companies improve their marketing strategies. Scraping Instagram followers can give insight into the age, location, gender, and interests of a user's followers.
    2. Competitive analysis: By scraping the followers of competitors, businesses can see what works for their competitors and what doesn't. This information can be used to develop better marketing strategies and improve their own social media presence.
    3. Influencer marketing: Scraping Instagram followers can help businesses identify potential influencers to partner with. By analyzing the followers of influencers, businesses can get a better understanding of the target audience they are reaching through influencer marketing.
    4. Data analysis: Scraping Instagram followers can provide a large amount of data that can be analyzed to uncover patterns and trends. This information can be used to make data-driven decisions about marketing and business strategy.

    It's worth noting that scraping Instagram followers is not officially supported by Instagram, and the platform has taken steps to prevent scraping in the past. Additionally, the use of automated tools to scrape data from the platform may violate Instagram's terms of service. Before scraping Instagram followers, it's important to carefully review and understand Instagram's policies to ensure that you're not breaking any rules.

    Structured vs. unstructured data

    Structured and unstructured data refer to the way that data is organized and stored.

    Structured data is organized in a well-defined format, such as a database table, CSV file, or spreadsheet. It typically consists of rows and columns, with each column representing a specific type of information and each row representing a single record. Structured data is easy to search, sort, and analyze because it has a clear structure and is easily accessible by software applications.

    Unstructured data, on the other hand, has no specific structure or format. It can take the form of images, audio files, videos, text documents, emails, or any other type of digital content that cannot be easily organized into a structured format. Unstructured data is often difficult to manage, process, and analyze because it does not have a clear structure or organization.

    In practice, many data sets contain a mix of structured and unstructured data. For example, a database may store structured data about customer orders, while also storing unstructured data such as customer feedback in the form of text documents or email messages.

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