How to Use a Proxy

Baidu is the leading search engine in China, and its organic listings hold information that is difficult to obtain elsewhere. This guide explains how to scrape Baidu search results using Python and proxies in a structured, repeatable manner, covering setup, parsing, pagination, storage, and scaling.

The objective is a practical pipeline. You will learn to send a search query, parse the returned HTML, extract titles and links, and store clean structured data. There are several ways to scrape Baidu organic results, and the approach below uses standard Python tools so the code remains readable.

Why scrape Baidu organic results

What Is a UDP proxy?

A UDP proxy is a type of proxy that forwards User Datagram Protocol traffic between a client and a server. It acts as an intermediary for UDP, accepting each UDP packet from the client and forwarding it toward the destination IP address and port.

The destination server sees the proxy server IP address rather than the original client. As a low-level proxy, UDP proxies do not interpret application data. They simply relay datagrams, which is what makes UDP proxies suitable for fast, real-time transmission. UDP proxies stay protocol agnostic, forwarding almost any packet without inspection.

UDP proxies differ sharply from http proxies. HTTP proxies were designed for web traffic, while UDP proxies are designed to move UDP packets. In practice, almost every UDP proxy today is a SOCKS5 proxy that implements the UDP ASSOCIATE command.

A proxy acts as an intermediary between a user and the wider network, but the direction it faces changes everything. The forward proxy vs reverse proxy question comes down to one thing: who the proxy represents.

This guide explains how each one works, where each fits, the trade-offs involved, and how to choose the right proxy for a given workload.

Both route traffic through an extra hop, yet they solve opposite problems. A clear grasp of the differences between forward and reverse proxies prevents costly architecture mistakes and keeps systems stable and measurable.

We work with thousands of clients who run web scraping, market research, ad verification, SEO monitoring, and large-scale automation projects. The question we hear most often is simple: which proxy type fits my workload – ISP or residential? In this guide we explain how isp and residential proxies operate, where each one performs best, and how to choose the right proxy for your needs. The choice between isp and residential proxies usually comes down to scale, speed, and how strict the target endpoint is about ip diversity.

Quick Comparison: ISP vs Residential Proxies

Below is a quick reference table that summarises how isp proxies and residential proxies differ across the parameters that matter most for performance testing and analytics workflows.

We provide both IPv4 and IPv6 proxies, and we know that picking the right type of IP address can be confusing. The choice of IP version affects pricing, compatibility, and performance for everything from data collection to ad verification. In this guide, we walk through the key differences between the two protocol versions and help you decide which one fits your project.

What Are IPv4 Proxies?

Whether you need to scrape thousands of keywords, run a rank tracker across multiple locations, or feed SERP data into your analytics pipeline, the proxy you choose directly affects data quality, success rate, and cost. Below you will find the best seo proxy providers compared on IP diversity, rotation, geo-targeting, API access, and value – everything professional seo teams need from proxies for rank tracking.

Whether you're a marketplace seller, a data analyst, or a developer building automated tools for e-commerce operations, understanding how to use proxies with eBay and Amazon is essential for working at scale. Both platforms are among the most technically protected online marketplaces in the world – they deploy multi-layer anti-bot systems, IP reputation scoring, rate limiting, and behavioral analysis to control automated access.

Without a well-configured proxy setup, large-scale data collection, price monitoring, and automation tasks become impossible. A proxy acts as an intermediary between your scraper or automated tool and the target platform, routing your requests through a different IP address and making each request appear as organic traffic. This guide will walk you through the key use cases, how to choose the right proxy type, and how to configure your tools for reliable, uninterrupted marketplace operations.

Choosing the right proxy type is one of the most important decisions for any online project. Whether you need to scrape data, manage multiple accounts, the differences between residential and datacenter proxies will directly affect your results. This comparison guide from Proxys.io covers datacenter vs residential proxies in detail, helping you select the best proxy technology for your particular use cases.

What Are Datacenter Proxies?

Datacenter proxies are IP addresses hosted in commercial data centers and operated independently of any internet service provider. Datacenter proxies use server-based infrastructure to route your traffic through high-performance machines. Datacenter IPs come from blocks assigned to hosting companies, which means they are not tied to a physical household or a real residential internet connection.

What Is Data Parsing and How It Works

Data parsing has become one of the most essential operations in modern information processing. At its core, data parsing is the process of taking raw, unstructured or semi-structured data and transforming it into a format that systems and people can work with. Parsing is a crucial step in any workflow that depends on accurate, timely information – from e-commerce analytics to financial reporting.

So what does data parsing means in practical terms? Data parsing is converting a string of data from one format into another that is easier to process. Parsing involves breaking input data into smaller pieces, labeling each piece, and reassembling the result data into a more readable and usable structure. The output is clean information ready for storage or downstream use.

Running a single account is easy; operating tens without getting flagged is a demanding feat. One that exposes the core challenge of today’s internet.

The reality is simple: web platforms don’t rely on IP tracking alone anymore. They combine IP signals with a layered set of hardware, software, and rendering traits that can’t be cleared like cookies. Once these signals align across accounts, platforms can connect activity instantly. This technique is called Browser fingerprinting.

Even with strong proxies, the same fingerprint can expose multiple accounts. This is exactly where Incogniton becomes essential. It adds a second layer of privacy protection by providing a fully-isolated browser, masking these fingerprints and closing the gap that proxies alone can’t fill.