- Framework: Node.js with Express.js
Rationale: Node.js with Express.js is cost-effective, widely adopted, and scales well. Its non-blocking I/O model and robust ecosystem make it ideal for building RESTful APIs and handling asynchronous operations, such as web scraping and email extraction.
- Approach: RESTful API design with versioning
Rationale:- RESTful APIs are straightforward, scalable, and widely understood.
- Versioning: We'll use URL versioning (e.g.,
/api/v1/...) to ensure future enhancements can be introduced without breaking existing integrations. - Naming Conventions: Standard, resource-oriented naming conventions will be applied (e.g.,
/api/v1/articles,/api/v1/users) for clarity and consistency.
- Approach: JSON Web Tokens (JWT) combined with Passport.js for multiple authentication strategies
Rationale:- Email/Password Authentication: Provides a traditional and secure way for users to create accounts and log in.
- Social Logins: Incorporating social authentication (e.g., Google, Facebook) offers users convenience and can help increase sign-up rates.
- Passport.js: This library supports a wide range of authentication strategies, making it a versatile choice for implementing both email/password and social logins.
- JWT: Once authenticated, JWTs will be used to securely manage sessions in a stateless manner.
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Web Scraping:
To keep costs low and use free, open-source solutions, we suggest the following:- Cheerio: A fast, lightweight library for parsing HTML and traversing the DOM in Node.js. It works similarly to jQuery and is ideal for extracting content from static pages.
- Axios: A promise-based HTTP client to make HTTP requests and retrieve webpage content.
- Puppeteer (Optional): For cases where target websites rely heavily on JavaScript to render content, Puppeteer (a headless Chrome Node API) can be used. It is open-source and free, though more resource-intensive compared to Cheerio.
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Email Extraction:
- Utilize simple regular expressions (regex) within Node.js to locate and extract email addresses from the scraped content.
- Alternatively, consider using lightweight libraries such as email-extractor if additional parsing features are needed.
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Content Analysis:
- Incorporate natural language processing (NLP) tools (e.g., Natural, compromise.js, or external NLP APIs) to extract keywords, subjects, and themes from user-submitted articles.
- Database: MongoDB with Mongoose ODM
Rationale:- MongoDB is a flexible, NoSQL document-based database that stores data in JSON-like documents.
- Mongoose provides an ODM layer to enforce schemas and validations, ensuring that documents are consistently formatted when passed across various modules (web scraping, content analysis, email extraction, etc.).
- This combination allows for rapid development and scalability while maintaining structured data flow throughout the application.