Wie man einen intelligenten RSS-Feed-Aggregator mit fortgeschrittener benutzerdefinierter Filterung erstellt

Einfache Zusammenfassung

An intelligent RSS Feed Aggregator that empowers users with customizable filters to curate their content streams efficiently and effectively.

Produktanforderungsdokument (PRD)

Goals:

• Develop a user-friendly RSS Feed Aggregator
• Implement advanced custom filtering capabilities
• Ensure scalability and security

Target Audience:

• Information professionals
• News enthusiasts
• Content curators
• Researchers

Key Features:

1. User authentication and profile management
2. RSS feed import and management
3. Custom filter creation and application
4. Real-time feed updates
5. Content categorization and tagging
6. Search functionality
7. Mobile-responsive design

User Requirements:

• Easy feed addition and removal
• Intuitive filter creation interface
• Fast loading and updating of feeds
• Ability to save and share filtered feeds
• Cross-platform accessibility

Benutzerflüsse

1. Feed Addition and Filtering:

   • User logs in
   • Navigates to "Add Feed" section
   • Enters RSS feed URL
   • Selects or creates custom filters
   • Saves and applies filters to the new feed

2. Content Browsing:

   • User accesses main dashboard
   • Views filtered feed content
   • Interacts with articles (read, save, share)
   • Adjusts filters in real-time

3. Filter Management:

   • User goes to "Manage Filters" section
   • Creates new filters based on keywords, authors, or categories
   • Edits existing filters
   • Applies filters to multiple feeds

Technische Spezifikationen

Frontend:

• React for component-based UI
• Redux for state management
• Axios for API requests
• Styled-components for CSS-in-JS

Backend:

• Node.js with Express.js framework
• PostgreSQL for database
• Sequelize as ORM
• JWT for authentication
• RSS Parser library for feed processing

APIs:

• REST API for client-server communication
• WebSockets for real-time updates

Testing:

• Jest for unit and integration testing
• Cypress for end-to-end testing

API-Endpunkte

• POST /api/auth/register
• POST /api/auth/login
• GET /api/feeds
• POST /api/feeds
• PUT /api/feeds/:id
• DELETE /api/feeds/:id
• GET /api/filters
• POST /api/filters
• PUT /api/filters/:id
• DELETE /api/filters/:id
• GET /api/articles
• POST /api/articles/save
• DELETE /api/articles/save/:id

Datenbankschema

Users:

• id (PK)
• username
• email
• password_hash
• created_at
• updated_at

Feeds:

• id (PK)
• user_id (FK)
• url
• title
• description
• last_fetched
• created_at
• updated_at

Filters:

• id (PK)
• user_id (FK)
• name
• type (keyword, author, category)
• value
• created_at
• updated_at

Articles:

• id (PK)
• feed_id (FK)
• title
• content
• author
• published_date
• link
• created_at
• updated_at

SavedArticles:

• id (PK)
• user_id (FK)
• article_id (FK)
• created_at

Dateistruktur

Implementierungsplan

1. Project Setup (1-2 days)

   • Initialize React app
   • Set up Node.js backend
   • Configure PostgreSQL database
   • Set up version control

2. Authentication (2-3 days)

   • Implement user registration and login
   • Set up JWT authentication
   • Create protected routes

3. Feed Management (3-4 days)

   • Develop feed addition and removal functionality
   • Implement RSS parsing and storage
   • Create feed listing and management interface

4. Custom Filters (4-5 days)

   • Design and implement filter creation interface
   • Develop filter logic and application to feeds
   • Create filter management system

5. Article Display and Interaction (3-4 days)

   • Design article list and detail views
   • Implement article saving and sharing features
   • Develop search functionality

6. Real-time Updates (2-3 days)

   • Implement WebSocket connection for live updates
   • Create background job for regular feed fetching

7. Testing and Refinement (3-4 days)

   • Write and run unit tests
   • Perform integration testing
   • Conduct user acceptance testing

8. Deployment and Documentation (2-3 days)

   • Set up production environment
   • Deploy application
   • Write user and technical documentation

Bereitstellungsstrategie

1. Choose a cloud provider (e.g., AWS, Google Cloud, or Heroku)
2. Set up a production database instance (e.g., Amazon RDS for PostgreSQL)
3. Configure environment variables for production
4. Set up a CI/CD pipeline using GitHub Actions or GitLab CI
5. Implement automated testing in the CI pipeline
6. Use Docker for containerization to ensure consistency across environments
7. Set up load balancing and auto-scaling for the backend
8. Implement CDN for static asset delivery
9. Configure monitoring and logging (e.g., ELK stack or Datadog)
10. Implement regular database backups
11. Set up SSL certificates for secure communication

Designbegründung

The chosen tech stack (React, Node.js, PostgreSQL) offers a balance of performance, scalability, and developer productivity. React's component-based architecture allows for modular and reusable UI elements, essential for a complex filtering system. Node.js provides a fast, event-driven backend capable of handling concurrent requests efficiently, which is crucial for real-time feed updates. PostgreSQL offers robust relational data management, necessary for complex queries involved in custom filtering.

The file structure separates concerns clearly, promoting maintainability and scalability. The implementation plan prioritizes core functionality first, allowing for iterative development and early user feedback. The deployment strategy focuses on scalability and reliability, ensuring the application can handle growing user bases and increasing amounts of RSS data.

Custom filters are implemented as a separate entity, allowing for flexible and powerful content curation. This design decision enables users to create complex filtering rules and apply them across multiple feeds, significantly enhancing the user experience and the app's value proposition.