Free Remote Proxy
Stable Proxies:
IP address | Port | Country | Protocol | Verified |
---|---|---|---|---|
172.67.72.188 | 80 | United States | http | 2 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 | 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
|
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
Reasons to monitor prices
There are several reasons why someone might choose to monitor prices, including:
1. Cost savings: By monitoring prices, consumers can be alerted to price drops or discounts, allowing them to save money on purchases.
2. Price comparison: Price trackers can be used to compare prices across multiple retailers and marketplaces, helping consumers find the best deals.
3. Market analysis: Price tracking can also be used for market analysis purposes, allowing businesses and individuals to keep track of trends and fluctuations in prices.
4. Price forecasting: Some price trackers provide price forecasting, using historical data to make predictions about future price movements. This information can be useful for making investment decisions.
5. Stock management: For businesses, price tracking can be used to monitor the prices of products or materials that are needed for production, allowing for better inventory management and cost control.
6. Price negotiation: Price tracking can also be used by businesses during price negotiations with suppliers, providing them with data on market prices to support their bargaining position.
Overall, price tracking can help individuals and businesses make informed decisions, save money, and stay ahead of price changes in the market.
How to Pull Data From Any Website?
There are several ways to extract data from a website:
1. Web scraping: This is a technique used to extract data from websites using a web scraper or a web crawling tool. A web scraper sends HTTP requests to a website, receives HTML responses, and extracts the desired data from the HTML code. The data can be stored in a structured format, such as a CSV file or a database.
2. APIs: Some websites provide APIs that allow you to retrieve data directly from their servers. An API (Application Programming Interface) is a set of rules that dictate how two software programs should interact with each other. You can use an API to send a request to the website's server and receive data in a standardized format, such as JSON.
3. Downloading data: Some websites allow you to download data in a structured format, such as CSV or Excel. You can download the data directly from the website and then use programming tools to process it as needed.
Each of these methods has its own advantages and disadvantages, and the best method for pulling data from a website depends on the specific requirements of your project.
What Is Data Quality?
Data quality refers to the level of accuracy, completeness, reliability, and relevance of data. It is an important aspect of data management and a critical component of decision-making in organizations. Poor data quality can lead to incorrect or misleading results, decreased efficiency, and decreased confidence in the data being used.
Data quality is influenced by a number of factors, including the source of the data, the data collection methods used, and the processes and systems used to manage the data. It is important to implement data quality control measures, such as data validation and verification, to ensure that the data being used is of high quality.
There are several dimensions of data quality, including:
1. Accuracy: This refers to the degree to which data accurately reflects the real-world values or events it is meant to represent.
2. Completeness: This refers to the extent to which data is complete, including the absence of missing or incomplete values.
3. Consistency: This refers to the degree to which data is consistent with other data within the same dataset or across different datasets.
4. Timeliness: This refers to the degree to which data is up-to-date and reflects current values or events.
5. Validity: This refers to the degree to which data conforms to specified business rules or constraints.
Improving data quality is an ongoing process that requires ongoing attention and effort, but the benefits of high-quality data are significant, including better decision-making, improved efficiency, and increased customer satisfaction.
How Do Concurrency and Parallelism Differ?
Concurrency and parallelism are related but distinct concepts in computer science.
Concurrency refers to the ability of a system to handle multiple tasks at the same time. This can be achieved by executing tasks in an overlapping manner, without necessarily executing them simultaneously. For example, a web server can handle multiple incoming requests concurrently by managing a queue of requests and processing one request at a time.
Parallelism, on the other hand, refers to the simultaneous execution of multiple tasks. This can be achieved by dividing a task into smaller subtasks and executing each subtask in parallel, either on different processors or cores of a single processor. Parallelism can significantly improve the performance of a system, by reducing the amount of time needed to complete a task.
In summary, concurrency and parallelism are related because parallelism can be used to achieve concurrency. By executing multiple tasks in parallel, a system can handle multiple tasks at the same time, and thus achieve concurrency. However, not all concurrency requires parallelism, as concurrency can also be achieved through other means, such as multitasking or time-sharing.
How to get unblocked from Craigslist?
If your IP address has been blocked by Craigslist, there are a few steps you can take to get unblocked:
1. Wait it out: Craigslist IP blocks are temporary and will typically resolve on their own within a few hours or days.
2. Contact Craigslist Support: You can try reaching out to Craigslist support and explain the situation. They may be able to help you get unblocked.
3. Change your IP address: You can try using a different IP address, such as a residential or mobile proxy, or disconnecting from your current internet connection and reconnecting to a different network.
4. Adjust your behavior: Make sure that your actions on Craigslist are in line with their terms of service and do not violate their policies.
It's important to note that Craigslist takes IP blocking seriously and repeated violations can result in permanent IP ban. To avoid getting blocked in the future, it's crucial to follow their terms of service and limit excessive or automated activity.
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