Parsing Proxy

Understanding the Concept of Parsing Proxy

Proxy servers act as intermediary nodes between a user’s web browser and the internet resource. They function as middlemen, receiving requests from the browser, forwarding them to the target sites, fetching the data, and routing it back to the client. This architecture allows the real IP address of the device to be concealed from the resource being accessed.

When parsing large volumes of data across various web resources, the use of a proxy becomes essential. Direct access from a single IP address to the target site is often restricted by the provider’s security rules and policies, slowing down the data collection process. Proxies help circumvent these limitations by creating the appearance of requests originating from different IP addresses.

Choosing the Right Proxy for Parsing

When selecting a proxy for parsing, several crucial factors must be considered:

Proxy Type

• Premium private proxies: Each IP address is dedicated exclusively to a single client, ensuring maximum anonymity and performance.
• Public proxies: Offered for free, but their use carries security risks and lower speeds due to the large number of connections.

Proxy Location

Proxies with IP addresses from the region of the target web resources can help bypass geographical restrictions during parsing. For instance, if you need to collect data from Russian websites, Russian IP proxies would be the optimal choice.

Proxy Protocols

Protocols determine the type of traffic that can be transmitted through a proxy. For parsing, the most common protocols are HTTP and SOCKS5 proxies. Their choice depends on the specific parsing tasks.

Number of Unique IP Addresses

The more unique IP addresses you use for parsing, the more evenly the load is distributed, making it harder for target web resources to detect and block the data collection process.

Performance and Bandwidth

To ensure high parsing speed, proxies must have sufficient bandwidth and low latency. This is especially important when working with scripts that send a large number of requests.

Integrating Proxy into Parsing

To use proxies for data parsing, they need to be integrated with your scripts or programs. The integration process may vary depending on the programming language or framework you use, but generally includes the following steps:

1. Choosing a library or module for working with proxies. For example, Python has the requests module with proxy support.

2. Configuring the proxy list. Usually, a pool of IP addresses is used, which are rotated with each request to enhance anonymity.

3. Implementing the proxy connection logic. This may involve automatically connecting to the next IP from the pool upon encountering access errors.

4. Handling errors and blockages. Monitoring the proxy status to promptly replace invalid IP addresses and prevent target resource blockages.

Here’s a simplified Python code example demonstrating the use of proxies with the requests module:

import requests

List of proxies

proxies = [‘http://123.45.67.89:8000’, ‘http://10.20.30.40:8080’]

Function for proxy rotation

def get_proxy():
proxy = proxies.pop(0)
proxies.append(proxy)
return {"http": proxy, "https": proxy}

Sending a GET request through a proxy

url = "https://example.com"
try:
response = requests.get(url, proxies=get_proxy(), timeout=10)
print(response.text)
except:
print("Error during parsing")


This example demonstrates a basic implementation of proxy rotation from a list when making an HTTP GET request.

Parsing JavaScript-Rendered Pages

When parsing websites where content is generated using JavaScript, different approaches are required, distinct from traditional HTTP requests. In this case, it may be necessary to incorporate a full-fledged web driver (e.g., Selenium or Puppeteer) and use specialized proxies compatible with it.

Example using Python + Selenium + proxy:


from selenium import webdriver
from selenium.webdriver.common.proxy import Proxy, ProxyType

Proxy configuration

proxy = Proxy()
proxy.proxy_type = ProxyType.MANUAL
proxy.http_proxy = "123.45.67.89:8000"
proxy.ssl_proxy = "123.45.67.89:8000"

Creating a driver with a proxy

capabilities = webdriver.DesiredCapabilities.CHROME.copy()
proxy.add_to_capabilities(capabilities)
driver = webdriver.Chrome(desired_capabilities=capabilities)

Parsing a JavaScript page

driver.get("https://example.com")
html = driver.page_source
print(html)
driver.quit()

This code configures a proxy for use with Selenium WebDriver and opens a JavaScript-rendered page through the proxy.

Conclusions

Using proxies enables efficient collection of large volumes of data from web resources, bypassing provider restrictions and enhancing the anonymity of the parsing process. Proper selection of proxy type, quantity, and location, as well as seamless integration with parsing scripts, are key factors for successful parsing. It’s also essential to consider the characteristics of the web resources from which data will be collected to choose the optimal methods and tools.

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Professional data parsing via ZennoPoster, Python, creating browser and keyboard automation scripts. SEO-promotion and website creation: from a business card site to a full-fledged portal.