Company Scraper Dashboard

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import logging
from gunicorn.app.base import BaseApplication
from app_init import create_initialized_flask_app

# Flask app creation should be done by create_initialized_flask_app to avoid circular dependency problems.
app = create_initialized_flask_app()

# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class StandaloneApplication(BaseApplication):
    def __init__(self, app, options=None):
        self.application = app
        self.options = options or {}
        super().__init__()

    def load_config(self):
        # Apply configuration to Gunicorn
        for key, value in self.options.items():
            if key in self.cfg.settings and value is not None:
                self.cfg.set(key.lower(), value)

    def load(self):
Get full code

Frequently Asked Questions

How can the Company Scraper Dashboard benefit e-commerce businesses?

The Company Scraper Dashboard can significantly benefit e-commerce businesses by providing up-to-date information on competitors and potential partners from billiger.de/Shops. By automating the scraping process, businesses can stay informed about new entrants, track changes in competitor profiles, and identify potential collaboration opportunities. This data can inform pricing strategies, market positioning, and partnership decisions, giving users of the Company Scraper Dashboard a competitive edge in the e-commerce landscape.

What security measures are in place to protect the data collected by the Company Scraper Dashboard?

The Company Scraper Dashboard implements several security measures to protect the collected data:

How can the Company Scraper Dashboard be customized for different industries or marketplaces?

While the current implementation of the Company Scraper Dashboard focuses on billiger.de/Shops, its modular design allows for easy customization to target different industries or marketplaces. To adapt the dashboard for other sources:

How can I add a new column to the companies table in the Company Scraper Dashboard?

To add a new column to the companies table, you need to create a new migration file and update the Company model. Here's how:

How can I modify the scraping logic in the Company Scraper Dashboard to handle pagination on billiger.de/Shops?

To handle pagination on billiger.de/Shops, you can modify the scrape_companies route in routes.py. Here's an example of how you might implement this:

```python @app.route("/api/scrape_companies", methods=["POST"]) def scrape_companies(): try: # ... (existing setup code)

       base_url = "https://www.billiger.de/shops"
       page = 1
       companies_data = []

       while True:
           url = f"{base_url}?page={page}"
           driver.get(url)
           driver.implicitly_wait(10)
           html_content = driver.page_source

           # Parse the HTML content with BeautifulSoup
           soup = BeautifulSoup(html_content, 'html.parser')

           # Use LLM to extract company information from the HTML content
           # ... (existing extraction code)

           companies_data.extend(result.get('companies', []))

           # Check if there's a next page
           next_page = soup.find('a', class_='next_page')
           if not next_page:
               break

           page += 1

       # Update database with companies_data
       # ... (existing database update code)

       return jsonify({"status": "success", "message": "Companies scraped successfully"})

   except Exception as e:
       # ... (existing error handling code)

```

This modification allows the Company Scraper Dashboard to iterate through all pages of results on billiger.de/Shops, ensuring comprehensive data collection.

Created: | Last Updated:

Web app for scraping company data from billiger.de/Shops, handling pagination, and storing information in a database.

Here's a step-by-step guide for using the Company Scraper Dashboard template:

Introduction

The Company Scraper Dashboard is a web application that allows you to scrape company data from billiger.de/Shops, handle pagination, and store the information in a database. It provides a user-friendly interface to view and manage the scraped company data.

Getting Started

  1. Click "Start with this Template" to begin using the Company Scraper Dashboard template in Lazy.

Test the Application

  1. Press the "Test" button in Lazy to deploy the application and launch the Lazy CLI.

Using the Company Scraper Dashboard

  1. Once the application is deployed, Lazy will provide you with a dedicated server link to access the dashboard. Open this link in your web browser.

  2. You'll be presented with the login page. Use your Google account to log in.

  3. After logging in, you'll see the main dashboard with the following sections:

  4. Home: Displays a welcome message
  5. Companies: Shows the list of scraped companies
  6. Team: Manages admin access to the dashboard

  7. Navigate to the "Companies" page to view the list of scraped companies.

  8. To scrape new company data:

  9. Click the "billiger.de scrapen" button on the Companies page
  10. The application will start scraping data from billiger.de/Shops
  11. Wait for the scraping process to complete
  12. The page will refresh automatically, showing the newly scraped company data

  13. The Companies table displays the following information for each company:

  14. Logo
  15. Name
  16. Website link
  17. Description
  18. Last updated timestamp

  19. To manage admin access:

  20. Go to the "Team" page
  21. Here you can add or remove admin emails and domain access

Integrating the Company Scraper Dashboard

The Company Scraper Dashboard is a standalone web application and doesn't require integration with external tools. However, you can use the scraped data in your own applications by accessing the SQLite database directly or by extending the application to include API endpoints for data retrieval.

By following these steps, you'll have a fully functional Company Scraper Dashboard that automatically scrapes and stores company data from billiger.de/Shops, providing an easy-to-use interface for viewing and managing the scraped information.



Template Benefits

  1. Automated Data Collection: This template provides a streamlined process for automatically scraping and updating company information from billiger.de/shops, saving significant time and effort compared to manual data gathering.

  2. Centralized Company Database: By storing scraped data in a structured database, the template creates a valuable, centralized repository of company information that can be easily accessed, analyzed, and utilized for various business purposes.

  3. User Management System: The built-in user authentication and authorization system, including allowlists and blocklists, ensures secure access control and enables efficient management of admin users across the organization.

  4. Customizable Dashboard: The template offers a flexible, responsive dashboard that can be easily customized to display relevant company data, providing quick insights and facilitating data-driven decision making.

  5. Scalable Web Application Architecture: Utilizing Flask, SQLAlchemy, and Gunicorn, the template provides a robust, scalable foundation for building and expanding web applications, making it suitable for growing businesses and evolving requirements.

Technologies

Flask Templates from Lazy AI – Boost Web App Development with Bootstrap, HTML, and Free Python Flask Flask Templates from Lazy AI – Boost Web App Development with Bootstrap, HTML, and Free Python Flask
Enhance Selenium Automation with Lazy AI: API Testing, Scraping and More Enhance Selenium Automation with Lazy AI: API Testing, Scraping and More
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