ML-Part Project

Overview

This repository is part of a larger web scraping project. It includes TypeScript functions designed to facilitate the extraction of product details from given URLs and integrate machine learning algorithms for data processing on the client side.

Functionality

The current implementation includes a TypeScript function that takes a URL as input and returns structured data extracted from the page. The data includes the product's name, category, vendor, price, currency, and delivery time.

Setup

To set up the project and install dependencies, run:

npm install

Usage

To use the web scraping function, import the scrapeProductDetails function from code.ts into your TypeScript or JavaScript file and call it with a valid URL.

import { scrapeProductDetails } from './path-to-code-ts';

// Replace 'your-product-url' with the actual product URL
scrapeProductDetails('your-product-url').then(data => {
  console.log(data);
}).catch(error => {
  console.error('Scraping failed', error);
});

Future Steps

To complete and enhance the functionality of this code, the following steps are suggested:

Integrate machine learning libraries, such as TensorFlow.js, to process the extracted data for pattern recognition or classification tasks.
Develop additional functions for error handling and validation of the scraped data to ensure robustness.
Implement a caching mechanism to store and reuse previously scraped data efficiently.
Design and integrate a front-end interface to allow non-technical users to input URLs and view the scraped data.
Coordinate with backend developers to ensure the scraped data can be stored and managed within the existing database infrastructure.

Assistance for Integration

If you need to integrate this function into the frontend or backend of your codebase, consider the following:

For frontend integration, ensure the function is called after validating the URL on the client side.
For backend integration, the function can be wrapped in an API endpoint to receive URLs and return the scraped data.

Please refer to the project's documentation or contact the repository maintainers for further assistance.