Parsing in C++: Power and Speed for Data Collection

Parsing in C++: When Speed is Everything

In the world of data collection, Python has long become mainstream. Requests, BeautifulSoup, Scrapy — these tools are familiar to anyone who has ever dealt with parsing. But what to do if you need to process thousands of pages per second, and server resources are not unlimited? Or if the project requires maximum performance and minimal memory consumption?

Then parsing in C++ takes the stage. Yes, this language is not as easy to learn as Python, but it gives what interpreted languages cannot — hardware-level speed and full control over memory. In this article, we will look at how to organize data scraping in C++, which libraries to use, and why C++ is sometimes the best choice for parsing.

Why Parsing in C++ is Not Madness?

Many believe that C++ is too complex for a task like collecting data from web pages. This is partly true: you can write a parser in Python in 15 minutes, but in C++ you will have to spend an hour. However, there are scenarios where C++ is indispensable:

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• High-load systems — when you need to parse millions of pages daily.
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• Microservices in C++ — if the entire backend is written in C++, it's easier to add a parser there as well.
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• Limited resources — embedded systems, IoT, where every megabyte counts.
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• Stability requirements — C++ allows you to avoid memory leak issues with the right approach.
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The key advantage of scraping in C++ is speed. Native code runs many times faster than Python, especially when working with regular expressions and parsing large HTML documents.

Toolkit for Parsing in C++

For working with HTTP requests and parsing HTML/XML, we will need proven libraries. Here is the essential toolkit for parsing websites in C++:

1. libcurl — Working with HTTP

libcurl is a Swiss Army knife for network requests. It supports HTTP/HTTPS, proxies, cookies, timeouts, and much more. It is the de facto standard for C++.

#include <curl/curl.h>\n#include <string>\n\nsize_t writeCallback(void* contents, size_t size, size_t nmemb, std::string* output) {\n    size_t totalSize = size * nmemb;\n    output->append((char*)contents, totalSize);\n    return totalSize;\n}\n\nstd::string fetchPage(const std::string& url) {\n    CURL* curl = curl_easy_init();\n    std::string response;\n    \n    if (curl) {\n        curl_easy_setopt(curl, CURLOPT_URL, url.c_str());\n        curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, writeCallback);\n        curl_easy_setopt(curl, CURLOPT_WRITEDATA, &response);\n        curl_easy_setopt(curl, CURLOPT_USERAGENT, "Mozilla/5.0");\n        \n        CURLcode res = curl_easy_perform(curl);\n        if (res != CURLE_OK) {\n            std::cerr << "curl error: " << curl_easy_strerror(res) << std::endl;\n        }\n        curl_easy_cleanup(curl);\n    }\n    return response;\n}

2. Gumbo-parser — HTML Parsing

Gumbo-parser from Google is a library for parsing HTML5, written in C. It is simple, fast, and has no dependencies. It is perfect for parsing HTML in C++.

#include <gumbo.h>\n#include <iostream>\n\nvoid extractLinks(GumboNode* node) {\n    if (node->type != GUMBO_NODE_ELEMENT) return;\n    \n    if (node->v.element.tag == GUMBO_TAG_A) {\n        GumboAttribute* href = gumbo_get_attribute(&node->v.element.attributes, "href");\n        if (href) {\n            std::cout << "Found link: " << href->value << std::endl;\n        }\n    }\n    \n    const GumboVector& children = node->v.element.children;\n    for (unsigned int i = 0; i < children.length; ++i) {\n        extractLinks(static_cast<G