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Kamila Mariyam · 2025-02-17T17:51:26+00:00

Introduction to Harvesting Product Data from Rozetka.com.ua In the digital age, data is a crucial asset for businesses aiming to understand market trends and consumer behavior. For companies targeting the Ukrainian market, Rozetka.com.ua stands out as a significant e-commerce platform offering a wealth of product data. This article explores how to harvest product data from Rozetka using C++ and MariaDB, focusing on aggregating electronics prices, descriptions, and customer reviews. This data can provide valuable insights for market analysis and strategic decision-making. Understanding the Importance of Product Data The Role of Product Data in Market Analysis Product data is essential for businesses to understand market dynamics and consumer preferences. By analyzing prices, descriptions, and customer reviews, companies can identify trends, assess competition, and tailor their offerings to meet consumer demands. In the context of the Ukrainian market, Rozetka.com.ua serves as a rich source of such data, particularly in the electronics sector. Accessing this data allows businesses to perform competitive analysis, price benchmarking, and sentiment analysis. These insights can drive marketing strategies, product development, and customer engagement efforts. Therefore, effectively harvesting and analyzing product data is a critical capability for businesses operating in the Ukrainian market. Challenges in Data Harvesting While the benefits of product data are clear, harvesting this data presents several challenges. Websites like Rozetka.com.ua often have complex structures and dynamic content, making it difficult to extract data efficiently. Additionally, legal and ethical considerations must be taken into account to ensure compliance with data protection regulations. Technical challenges include handling large volumes of data, managing data quality, and integrating data from various sources. To overcome these challenges, businesses need robust tools and methodologies, such as web scraping techniques using C++ and database management with MariaDB. Web Scraping with C++ Setting Up the Environment To begin harvesting data from Rozetka.com.ua, a suitable development environment is necessary. C++ is a powerful language for web scraping due to its performance and flexibility. Setting up the environment involves installing a C++ compiler and necessary libraries, such as libcurl for handling HTTP requests and HTML parsing libraries like Gumbo or Beautiful Soup. Once the environment is set up, the next step is to write a C++ program that can send HTTP requests to Rozetka.com.ua, retrieve HTML content, and parse the required data fields. This involves understanding the website's structure and identifying the HTML elements containing the desired information. Implementing the Web Scraper The core of the web scraping process is the implementation of a C++ program that can efficiently extract data from Rozetka.com.ua. The following code snippet demonstrates a basic implementation using libcurl to fetch HTML content and a simple parser to extract product prices, descriptions, and reviews. #include #include #include #include size_t WriteCallback(void* contents, size_t size, size_t nmemb, void* userp) { ((std::string*)userp)->append((char*)contents, size * nmemb); return size * nmemb; } void fetchData(const std::string& url) { CURL* curl; CURLcode res; std::string readBuffer; curl curl_easy_init(); if(curl) { curl_easy_setopt(curl, CURLOPT_URL, url.c_str()); curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, WriteCallback); curl_easy_setopt(curl, CURLOPT_WRITEDATA, &readBuffer); res curl_easy_perform(curl); curl_easy_cleanup(curl); // Simple regex to extract product data std::regex priceRegex("(\d+)"); std::smatch match; if (std::regex_search(readBuffer, match, priceRegex)) { std::cout << "Price: " << match << std::endl; } } } int main() { std::string url "https://rozetka.com.ua/some-product-page"; fetchData(url); return 0; } This code snippet demonstrates how to fetch HTML content from a product page on Rozetka.com.ua and extract the price using a regular expression. Similar techniques can be applied to extract other data fields, such as product descriptions and customer reviews. Storing Data with MariaDB Setting Up MariaDB Once the data is extracted, it needs to be stored in a structured format for analysis. MariaDB is an excellent choice for this purpose due to its performance, scalability, and compatibility with MySQL. Setting up MariaDB involves installing the database server and configuring it to accept connections from the C++ application. After installation, a database schema must be designed to store the product data. This includes creating tables for products, prices, descriptions, and reviews, with appropriate data types and relationships. The following SQL script demonstrates how to create a basic schema for storing product data. CREATE DATABASE rozetka_data; USE rozetka_data; CREATE TABLE products ( id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(255) NOT NULL, description TEXT, price DECIMAL(10, 2), review_count INT ); CREATE TABLE reviews ( id INT AUTO_INCREMENT PRIMARY KEY, product_id INT, review_text TEXT, FOREIGN KEY (product_id) REFERENCES products(id) ); This script creates a database named "rozetka_data" with two tables: "products" and "reviews". The "products" table stores basic product information, while the "reviews" table stores customer reviews linked to the corresponding product. Inserting Data into MariaDB With the database schema in place, the next step is to insert the extracted data into MariaDB. This involves establishing a connection between the C++ application and the database, and executing SQL INSERT statements to populate the tables with product data. The following C++ code snippet demonstrates how to connect to MariaDB and insert product data using the MySQL C API. #include #include void insertProductData(const std::string& name, const std::string& description, double price, int reviewCount) { MYSQL* conn; MYSQL_RES* res; MYSQL_ROW row; conn mysql_init(NULL); if (conn NULL) { std::cerr << "mysql_init() failedn"; return; } if (mysql_real_connect(conn, "localhost", "user", "password", "rozetka_data", 0, NULL,

Harvesting Product Data from Rozetka.com.ua Using C++ & MariaDB: Aggregating Electronics Prices, Descriptions, and Customer Reviews for Ukrainian Market Analysis

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