Сливаю рабочую тему заработка на парсинге | Кейс Wildberries (Часть 1)

Introduction

In this tutorial, we will explore a practical method for earning money through data scraping, specifically using the Wildberries platform. The tutorial will guide you through the process of creating a data extraction program, which can be used for generating data exports that can be sold on freelance platforms. This is part one of a series focused on this approach.

Step 1: Understanding Wildberries

• Familiarize yourself with the Wildberries platform.
• Explore the types of data available for scraping, such as product details, pricing, and stock information.
• Identify potential use cases for the data you will collect, such as market analysis or price comparison.

Step 2: Acquiring Proxies

• Understand the need for proxies in data scraping to avoid IP bans.
• Research reliable proxy providers; consider using mobile proxies for better anonymity.
• Sign up for a proxy service. You can find a recommended provider here.
• Test your proxies to ensure they are functioning properly before proceeding.

Step 3: Writing the Code

• Set up your development environment with Python and necessary libraries for web scraping (e.g., BeautifulSoup, Requests).
• Start by importing the required libraries:

  import requests
  from bs4 import BeautifulSoup
  

• Write a basic function to fetch data from Wildberries:

  def fetch_data(url):
      response = requests.get(url)
      return response.text
  

• Parse the HTML content using BeautifulSoup:

  def parse_data(html):
      soup = BeautifulSoup(html, 'html.parser')
      products = soup.find_all(class_='product-card')
      for product in products:
          title = product.find(class_='product-title').text
          price = product.find(class_='product-price').text
          print(f'Title: {title}, Price: {price}')
  

Step 4: Running the Scraper

• Integrate the fetching and parsing functions:

  url = 'https://www.wildberries.ru/catalog'
  html = fetch_data(url)
  parse_data(html)
  

• Execute your script and review the output for data accuracy.
• Make adjustments as necessary to improve data collection.

Step 5: Selling Data Exports

• Once you have successfully collected and formatted your data, consider selling it on freelance platforms.
• Explore marketplaces like Kwork for potential clients looking for data services. You can find Kwork here.
• Create a portfolio showcasing your data scraping capabilities to attract buyers.

Conclusion

This tutorial provided a foundational approach to earning money through data scraping on Wildberries. We covered understanding the platform, acquiring proxies, writing the scraping code, and launching your project. As you continue, focus on refining your code and gathering quality data to maximize your earning potential. In the next part of the series, we will delve deeper into advanced techniques and optimizations for your scraper.