C++ Web Scraping Guide 2026

Setting up your C++ scraping environment

Before you start writing scraping code, you need to install the main libraries. The setup steps depend on your operating system.

1. Windows

The simplest way to manage C++ scraper libraries on Windows is to use vcpkg, which is Microsoft's open-source package manager.

Installing vcpkg:

git clone https://github.com/microsoft/vcpkg
cd vcpkg
bootstrap-vcpkg.bat

Installing the libraries:

vcpkg install curl libxml2 cpr pugixml 
vcpkg integrate install

2. macOS

On macOS, you can use Homebrew to install the required libraries:

brew install curl libxml2 cpr pugixml cmake

If you're using CMake, add the Homebrew prefix to your build config:

export PKG_CONFIG_PATH="/opt/homebrew/lib/pkgconfig"

3. Linux (Ubuntu/Debian)

On Linux, use apt to install dependencies:

sudo apt update
sudo apt install libcurl4-openssl-dev libxml2-dev libpugixml-dev cmake

For CPR, build from source using CMake:

git clone https://github.com/libcpr/cpr.git
cd cpr && mkdir build && cd build
cmake .. && make && sudo make install

CMake Configuration

No matter which platform you use, add the following lines to your CMakeLists.txt file:

find_package(cpr REQUIRED)
find_package(LibXml2 REQUIRED)
target_link_libraries(your_project cpr::cpr LibXml2::LibXml2)

If your project also uses libcurl directly (rather than through CPR), add find_package(CURL REQUIRED) and link CURL::libcurl as well.

How to build a C++ web scraper

In this tutorial, you will build a scraper that collects product data from the Oxylabs Sandbox e-commerce site, which is a safe and public site for practicing scraping. You will extract product names, prices, and descriptions, and then save the results to a CSV file.

We’ll use CPR for HTTP requests and libxml2 for HTML parsing. pugixml is not used in this tutorial, but it is worth having installed if you work with XML-heavy sources like sitemaps or RSS feeds.

Step 1: Initialize the project

If you use macOS or Linux, start by creating your project folder and a CMakeLists.txt file like this: 

mkdir cpp-scraper && cd cpp-scraper
touch main.cpp CMakeLists.txt

On Windows, create the folder and files manually or use your IDE to set up the project. Add the following to CMakeLists.txt

cmake_minimum_required(VERSION 3.14)
project(cpp_scraper)
set(CMAKE_CXX_STANDARD 17)

find_package(cpr REQUIRED)
find_package(LibXml2 REQUIRED)

add_executable(cpp_scraper main.cpp)
target_link_libraries(cpp_scraper cpr::cpr LibXml2::LibXml2)

Step 2: Make an HTTP Request

Use CPR to fetch the page HTML code. Open main.cpp and start with this:

#include <iostream>
#include <cpr/cpr.h>
int main() {
    cpr::Response response = cpr::Get(
        cpr::Url{"https://sandbox.oxylabs.io/products"},
        cpr::Header{{"User-Agent", "Mozilla/5.0"}}
    );
    if (response.status_code == 200) {
        std::cout << "Page fetched successfully." << std::endl;
        std::cout << response.text << std::endl;
    } else {
        std::cerr << "Request failed: " << response.status_code << std::endl;
    }

    return 0;
}

Here, CPR handles the HTTP connection, headers, and response, so you don't need any manual socket management.

Step 3: Parse the HTML

Pass the response body to libxml2 for parsing. Add the following includes and update main.cpp:

#include <libxml/HTMLparser.h>
#include <libxml/xpath.h>

htmlDocPtr doc = htmlReadMemory(
    response.text.c_str(),
    response.text.size(),
    nullptr, nullptr,
    HTML_PARSE_NOERROR | HTML_PARSE_NOWARNING
);

if (!doc) {
    std::cerr << "Failed to parse HTML." << std::endl;
    return 1;
}

Here, htmlReadMemory parses the raw HTML string into a document tree you can query.

Step 4: Extract data with XPath

Use XPath to target specific elements: product names, prices, and descriptions to collect data:

xmlXPathContextPtr context = xmlXPathNewContext(doc);

// Extract product titles
xmlXPathObjectPtr titles = xmlXPathEvalExpression(
    (xmlChar*)"//h4[@class='product-title']",
    context
);

if (titles && titles->nodesetval) {
    for (int i = 0; i < titles->nodesetval->nodeNr; i++) {
        xmlNodePtr node = titles->nodesetval->nodeTab[i];
        xmlChar* content = xmlNodeGetContent(node);
        std::cout << "Product: " << content << std::endl;
        xmlFree(content);
    }
}

You can adjust the XPath selectors to match the actual HTML structure of your target page.

Step 5: Store the data

With your data extracted, write it to a CSV file:

#include <fstream>
#include <algorithm>

// Extract prices and descriptions (titles already extracted in Step 4)
xmlXPathObjectPtr prices = xmlXPathEvalExpression(
    (xmlChar*)"//span[@class='product-price']",
    context
);
xmlXPathObjectPtr descs = xmlXPathEvalExpression(
    (xmlChar*)"//p[@class='product-description']",
    context
);

std::ofstream file("products.csv");
file << "Title,Price,Description\n";

if (titles && titles->nodesetval &&
    prices && prices->nodesetval &&
    descs  && descs->nodesetval) {

    int count = std::min({
        titles->nodesetval->nodeNr,
        prices->nodesetval->nodeNr,
        descs->nodesetval->nodeNr
    });

    for (int i = 0; i < count; i++) {
        xmlChar* titleXml = xmlNodeGetContent(titles->nodesetval->nodeTab[i]);
        xmlChar* priceXml = xmlNodeGetContent(prices->nodesetval->nodeTab[i]);
        xmlChar* descXml  = xmlNodeGetContent(descs->nodesetval->nodeTab[i]);

        std::string title = (char*)titleXml;
        std::string price = (char*)priceXml;
        std::string desc  = (char*)descXml;

        file << "\"" << title << "\",\"" << price << "\",\"" << desc << "\"\n";

        xmlFree(titleXml);
        xmlFree(priceXml);
        xmlFree(descXml);
    }
}

file.close();
std::cout << "Data saved to products.csv" << std::endl;

// Clean up
xmlXPathFreeObject(titles);
xmlXPathFreeObject(prices);
xmlXPathFreeObject(descs);
xmlXPathFreeContext(context);
xmlFreeDoc(doc);

You should find a products.csv file in your project folder with the scraped product data.

Advanced C++ web scraping techniques

After you have the basics working, you may find that a simple HTTP request is not always enough. Here are some ways to handle common challenges:

Handling JavaScript-rendered pages

Many modern websites load content dynamically, so the HTML you fetch may not include the data you need. Since C++ does not have a built-in headless browser library, you have a few options:

Option 1: Use Selenium via its WebDriver API
You can send HTTP requests directly to a running Selenium WebDriver server and retrieve the fully rendered HTML:

// Start ChromeDriver separately, then talk to it via HTTP
cpr::Response session = cpr::Post(
    cpr::Url{"http://localhost:9515/session"},
    cpr::Header{{"Content-Type", "application/json"}},
    cpr::Body{R"({"capabilities":{"browserName":"chrome"}})"}
);

Option 2: Use a Scraping API The simpler route is to offload JavaScript rendering to a managed API like Web Scraper API. You send a request, and get back fully rendered HTML, so no browser management needed:

cpr::Response response = cpr::Post(
    cpr::Url{"https://realtime.oxylabs.io/v1/queries"},
    cpr::Authentication{"YOUR_USERNAME", "YOUR_PASSWORD", cpr::AuthMode::BASIC},
    cpr::Header{{"Content-Type", "application/json"}},
    cpr::Body{R"({
        "source": "universal",
        "url": "https://your-target-site.com",
        "render": "html"
    })"}
)

Managing sessions and cookies

If you are scraping sites that require login or track user state, you need to keep cookies between requests. CPR makes this simple by letting you use a shared session object:

#include <cpr/cpr.h>

// Create a persistent session
cpr::Session session;
session.SetUrl(cpr::Url{"https://example.com/login"});
session.SetHeader(cpr::Header{{"Content-Type", "application/x-www-form-urlencoded"}});
session.SetBody(cpr::Body{"username=myuser&password=mypass"});

// Log in — cookies are stored automatically
cpr::Response login = session.Post();

// Reuse the same session for authenticated requests
session.SetUrl(cpr::Url{"https://example.com/dashboard"});
cpr::Response dashboard = session.Get();

std::cout << dashboard.text << std::endl;

When you use a single cpr::Session object, cookies are automatically kept between requests, so you do not need to parse cookies manually.

Multithreading for large-scale scraping

C++ gives you direct access to threading, making it a good choice for scraping multiple pages at the same time. You can use std::thread to run requests concurrently:

#include <iostream>
#include <thread>
#include <vector>
#include <cpr/cpr.h>

void scrape_page(const std::string& url) {
    cpr::Response response = cpr::Get(
        cpr::Url{url},
        cpr::Header{{"User-Agent", "Mozilla/5.0"}}
    );

    if (response.status_code == 200) {
        std::cout << "Scraped: " << url << " (" 
                  << response.text.size() << " bytes)" << std::endl;
    }
}

int main() {
    std::vector<std::string> urls = {
        "https://sandbox.oxylabs.io/products?page=1",
        "https://sandbox.oxylabs.io/products?page=2",
        "https://sandbox.oxylabs.io/products?page=3",
        "https://sandbox.oxylabs.io/products?page=4"
    };

    std::vector<std::thread> threads;

    for (const auto& url : urls) {
        threads.emplace_back(scrape_page, url);
    }

    // Wait for all threads to finish
    for (auto& t : threads) {
        t.join();
    }

    return 0;
}

Here’s a couple of things you should keep in mind when multithreading:

• Protect shared data. If multiple threads write to the same data structure, use std::mutex to avoid race conditions.

• Don't go too wide. Spinning up too many threads at once can trigger rate limits. Start with 4-8 concurrent threads and adjust based on the target website's tolerance.

• Add delays between requests. Even with multiple threads, spacing out requests reduces the chance of getting blocked.

• Use rotating proxies. At scale, sending many requests from a single IP will get you blocked. Pair your multithreaded scraper with rotating proxies to distribute requests across different IPs and avoid bans.

Bypassing CAPTCHA and anti-scraping measures

Most websites have measures in place to limit automated access. Here's what you'll commonly run into and how to handle it responsibly.

• Rate limiting is the most common. If you send too many requests too fast, the server will start blocking you. The fix is simple – you should add delays between requests:

#include <thread>
#include <chrono>

// Wait 2 seconds between requests
std::this_thread::sleep_for(std::chrono::seconds(2));

• User-Agent detection is another quick filter. Always set a realistic User-Agent header so your requests don't immediately stand out:

cpr::Header{{"User-Agent", "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}}

• IP blocking kicks in when too many requests come from the same address. Pair your scraper with rotating proxies to distribute traffic across multiple IPs.

• CAPTCHAs are harder to deal with in C++ directly. Your practical options are:

• Use a managed scraping API like Web Scraper API, which handles CAPTCHA solving on the backend

• Integrate a third-party CAPTCHA solving service via their HTTP API

One important thing to remember: always check a site’s robots.txt and terms of service before scraping. Ignoring technical blocks on sites that forbid scraping can have legal consequences.

Limitations of web scraping with C++

C++ is a capable scraping tool in the right context, but it comes with real trade-offs. For example: 

• No dedicated scraping libraries. You're combining general-purpose libraries that weren't built for scraping. That means more glue code and more maintenance compared to Python's ready-made ecosystem.

• No native JavaScript rendering. There's no headless browser built in. Scraping JS-heavy sites requires external workarounds or a managed API.

• Slower development. Verbose syntax, manual compilation, and memory management slow you down. What takes 10 lines in Python can take 40 in C++.

• Smaller scraping community. Most tutorials and community knowledge assume Python or JavaScript. Troubleshooting in C++ means fewer ready answers online.

That said, if your project genuinely needs high throughput or tight resource constraints (and your team already knows C++) the trade-offs can be worth it.

C++ web scraping alternatives

If C++ feels like too much overhead for your project, these languages have dedicated scraping ecosystems and plenty of community support: 

• Python: the most popular choice. Libraries like Scrapy, BeautifulSoup, and Playwright make it easy to get started and scale up.

• JavaScript/Node.js: a natural fit if you're scraping JS-heavy sites. Puppeteer and Playwright are both excellent options.

• Java: solid for enterprise environments. Jsoup handles HTML parsing cleanly and integrates well with existing Java infrastructure.

• C#: a good pick if your team works in the .NET ecosystem. HtmlAgilityPack and Playwright for .NET are the go-to tools.

• PHP: works well for quick scraping tasks, especially if you're already running a PHP stack.

If you'd rather skip managing infrastructure altogether, Web Scraper API handles requests, rendering, and anti-bot measures on the backend, with no library setup or proxy management required.

Conclusion

C++ web scraping makes sense in specific situations – high-volume pipelines, performance-critical data collection, or projects where your team is already working in C++. For most use cases though, the setup overhead and lack of dedicated tooling make other languages a more practical starting point.

If you choose C++, use libcurl or CPR for making requests, libxml2 or pugixml for parsing, and rotating proxies to handle scaling. If managing infrastructure becomes too complex, the Web Scraper API offers a simple way to handle the hard parts for you.