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https://github.com/kostas-python/scrape-app2

Works on Localhost for vrisko.gr website
https://github.com/kostas-python/scrape-app2

nextjs puppeteer shadcn-ui tailwindcss typescript

Last synced: 7 days ago
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Works on Localhost for vrisko.gr website

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README

        

This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app).

## Getting Started

First, run the development server:

```bash
npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev
```

Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.

You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file.

This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel.

## Learn More

To learn more about Next.js, take a look at the following resources:

- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API.
- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial.

You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome!

## Deploy on Vercel

The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js.

Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details.

******
Built with Next.js, TypeScript, Puppeteer, and ShadCN/UI, this web scraping application efficiently extracts structured business data while bypassing bot detection using the Stealth plugin. It supports multi-page navigation, dynamically follows pagination, and ensures robust error handling to prevent crashes or data loss.

The scraper extracts key details such as business name, address, occupation, email, website, and phone number from multiple listing formats, normalizing the data for consistency. The extracted data is processed, structured, and exported as a CSV file, ensuring compatibility with various data analysis tools.

The UI, built with ShadCN/UI and Tailwind CSS, provides a clean and responsive interface for managing scraping tasks. API routes in Next.js handle requests efficiently, leveraging serverless functions for optimized performance. The application is deployed on Vercel for scalability and fast global access.

This project demonstrates expertise in web automation, data extraction, API development, UI/UX design, and cloud deployment, showcasing the ability to build efficient, scalable, and user-friendly web applications.

***local host only