Python Guide: Scraping Google Search Results

This article analyzes in detail the complete technical path of using Python to automatically crawl Google search results, covering core tool selection, anti-crawling breakthrough solutions and proxy service integration strategies, providing a systematic solution for compliant data collection.

1. Technical challenges and core logic of Google search crawling

The dynamic rendering mechanism and anti-crawling strategy of Google search results pages form a triple technical barrier:

Dynamic DOM loading: 90% of the content is loaded asynchronously via JavaScript, which cannot be directly parsed by traditional request libraries

Request fingerprint detection: Identify abnormal Header features (such as unconventional User-proxy) to trigger verification code

IP frequency limit: A single IP with more than 50 requests per day may trigger a temporary ban

abcproxy's proxy IP pool provides infrastructure support for large-scale data collection through a million-level residential IP rotation mechanism.

2. Selection and implementation of key technology stack

2.1 Request Library Performance Comparison

Requests: Synchronous request library, suitable for small-scale crawling (≤100 pages/day)

aiohttp: asynchronous framework, throughput increased by 5-8 times, needs to be used with asyncio event loop

Scrapy: a full-featured framework with built-in middleware that supports automatic retries and proxy integration

2.2 Dynamic Rendering Solution

Selenium: Full browser environment simulation, high resource consumption (single instance occupies ≥ 500MB of memory)

Playwright: Cross-browser support, built-in intelligent waiting mechanism to reduce the risk of timeout

Pyppeteer: Lightweight implementation of Chrome DevTools Protocol, reducing memory usage by 40%

2.3 Data analysis optimization

BeautifulSoup: supports multiple parsers (lxml/html5lib), suitable for static pages

Parsel: Scrapy-specific selector, integrating XPath and CSS mixed syntax

Textract: PDF/image and other unstructured data extraction tools

3. Four-layer protection system of anti-crawl strategy

3.1 Request Header Camouflage Technology

Build a dynamic Header pool, including:

200+ real browser User-proxy rotation

Randomize Accept-Language parameter (en-US, zh-CN, etc.)

Simulate Referer jump chain (Google site navigation path)

3.2 Behavioral fingerprint simulation

Random scrolling page depth (0-2000px range)

Differentiated click delay (1.2-3.5 seconds normal distribution)

Simulate the movement trajectory of human cursor (Bezier curve algorithm)

3.3 Proxy IP Configuration Solution

Residential proxy: simulates real user geographical distribution (abcproxy static ISP proxy recommended)

Intelligent switching strategy: dynamically adjust the IP pool according to the response status code

Concurrency control: single IP request interval ≥ 15 seconds, daily average usage ≤ 30 times

3.4 Verification code breakthrough mechanism

OCR recognition: Tesseract engine + custom font training

Third-party API integration: 2Captcha/DeathByCaptcha commercial services

Verification diversion: Automatically switch proxy channels when verification is triggered

4. Data storage and cleaning specifications

4.1 Structured Storage Model

Designing a MongoDB document structure includes:

{

"keyword": "python proxy",

"rank": 12,

"title": "abcproxy official website-professional proxy IP service provider",

"snippet": "Provide full-scenario solutions such as residential proxy and data center proxy...",

"link": "https://abcproxy.com",

"cache_time": "2025-03-07T06:22:15Z"

}

(Note: The actual code needs to be adjusted according to the library syntax)

4.2 Deduplication Optimization Algorithm

SimHash generates 64-bit page fingerprints

Redis Bloom filter implements millisecond-level duplicate checking

Text similarity calculation (Jaccard coefficient ≥ 0.85 is considered duplicate)

4.3 Incremental crawling strategy

Time series filtering based on the modified_time field

Prioritize updating records with ranking fluctuations > ±5 digits

Automatically identify and skip broken links that have 404

5. Three-dimensional guarantee mechanism for compliance operation

5.1 Protocol layer compliance

Strictly follow the Crawl-delay setting in robots.txt

Disable sensitive parameters (such as site:, filetype: and other advanced operators)

Control the proportion of single domain name requests to ≤ 30% of the total traffic

5.2 Data security protection

AES-256 encrypted storage of raw HTML

Data anonymization (removing user identification information)

Access log retention period ≤ 72 hours

5.3 Service Stability Design

Distributed crawler cluster deployment (at least 3 nodes for redundancy)

Fuse mechanism: automatically suspend tasks if error rate > 15%

Proxy service health check (abcproxy API real-time monitoring of IP availability)

As a professional proxy IP service provider, abcproxy provides a variety of high-quality proxy IP products, including residential proxy, data center proxy, static ISP proxy, Socks5 proxy, unlimited residential proxy, suitable for a variety of application scenarios. If you are looking for a reliable proxy IP service, welcome to visit the abcproxy official website for more details.