Free Proxy Provider
Stable Proxies:
IP address | Port | Country | Protocol | Verified |
---|---|---|---|---|
172.67.72.188 | 80 | United States | http | 5 hours 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 | 3 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 | 5 days 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 | 6 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 | 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 | 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
|
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 Telegram group members?
Scraping Telegram group members can be accomplished programmatically using the Telegram Bot API. To do this, you'll need to create a bot account, obtain an API key, and use the API to extract information about the members of a Telegram group.
Here are the basic steps to scrape Telegram group members:
1. Create a bot account: To access the Telegram Bot API, you need to create a bot account and obtain an API key. You can do this by talking to the BotFather bot on Telegram and following the steps to create a new bot.
2. Get the group chat ID: In order to extract information about the members of a Telegram group, you need to know the chat ID of the group. You can obtain the chat ID by using the getUpdates method from the Telegram Bot API and looking at the response.
3. Use the Telegram Bot API to get group members: Once you have the chat ID, you can use the getChatMembersCount method from the Telegram Bot API to get the number of members in the group. You can then use the getChatMembers method to get information about each member, such as their user ID and username.
4. Extract the desired information: You can extract the desired information about the members, such as their username, user ID, and status, and store it in a data structure for later use.
Note that scraping Telegram group members may violate the terms of service of Telegram, so be sure to review their policies before proceeding. Additionally, you should be mindful of the rate limits imposed by the Telegram Bot API, as excessive usage can result in your API key being blocked.
What can you do with TikTok proxies?
TikTok proxies can be used for a variety of purposes, including:
1. Accessing restricted TikTok content: If you are located in a region where TikTok is restricted or censored, you can use a TikTok proxy to bypass these restrictions and access all of the app's content.
2. Protecting your online privacy: By using a TikTok proxy, you can hide your real IP address and location, making it more difficult for others to track your online activities. This can help to protect your privacy and keep your online activities private.
3. Scraping TikTok data: If you need to collect data from TikTok, such as user profiles or hashtags, a TikTok proxy can help you do so without getting blocked or rate-limited by the app's servers.
4. Improving your TikTok performance: Some TikTok proxies can help to improve the performance of the app, such as reducing lag or buffering times.
It's important to note that while TikTok proxies can provide these benefits, it's important to choose a reliable and trustworthy proxy provider to ensure that your online privacy and security are not compromised.
How to avoid honeypots during data collection
To avoid honeypots during data collection, you should follow these best practices:
1. Conduct research: Before you start collecting data, research the target system or network to determine if there are any known honeypots or decoys that you should be aware of. Check the web and forums for any information that might help you identify these decoys.
2. Verify the source: Before you download any data or software, verify the source and make sure that it is reputable and reliable. Avoid downloading data or software from untrusted sources, such as unknown websites or peer-to-peer networks.
3. Use encryption: If you are collecting sensitive data, use encryption to protect the data during transit. This will make it more difficult for anyone to intercept or tamper with the data.
4. Monitor activity: Regularly monitor your activity to detect any suspicious behavior or signs of compromise. If you notice anything out of the ordinary, stop your data collection immediately and take steps to secure your system.
5. Keep software updated: Make sure that your operating system and all of the software you are using are up-to-date and patched. Attackers often exploit known vulnerabilities in software to compromise systems.
6. Be cautious: Be cautious when collecting data, especially when working with sensitive information. Use common sense and exercise good judgment to avoid falling victim to honeypots or other security traps.
By following these best practices, you can reduce the risk of encountering honeypots during data collection and help to ensure the security and privacy of the data you collect.
What benefits can a well-chosen programming language bring?
A well-chosen programming language can bring several benefits, including:
Productivity: A language that is well-suited to the task at hand can lead to increased developer productivity and faster time-to-market.
Maintainability: A language with a clean and expressive syntax can make the code easier to maintain over time.
Portability: A language that runs on multiple platforms can reduce the cost of porting the code to new systems.
Community: A widely-used language is likely to have a large and active community, providing a wealth of resources, libraries, and support.
Performance: Some languages are designed with performance in mind and can provide faster execution times or lower resource usage.
Hiring: Choosing a popular language can make it easier to find and hire developers with the required skills.
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.
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