Sentimentify, the app who analyze your tweets :)
The architecture was built using the concepts of Clean Architecture and the SOLID principles. The modularization was composed by:
- SentimentifyEngine: Domain and presentation layers of Search and Analyze features plus abstractions of data layer, like HTTP client.
- SentimentifyiOS: User interface implementation of Search and Analyze features using UIKit.
- TwitterSearchInfrastructure: Infrastructure details of how to do a twitter request, how authenticate and how map the data. Implements the SearchLoader protocol and add behaviour of tweets search.
- GoogleAnalyzeInfrastructure: Infrastructure details of how to do a natural language request, how authenticate and how map the data. Implements both AnalyzeLoader and AnalyzeClassifier protocol, and add behaviour of analyze sentiment and classify the content.
- SentimentifyTestExtensions: Add extra behaviours specific for unit tests.
- SentimentifyApp: The main module, that create features and inject the dependencies, control the navigation flow, add new behaviours trough decorators and adapters.
demo.mov
Features
- Search and list the latest tweets
- See the emotion result based on selected tweet
Non-functional features
- Clean Architecture
- SOLID Principles
- Unit Tests using TDD
- Modular projects using Frameworks
- Design Patterns (Strategy, Proxy, Decorator and Adapter)
- Twitter and Google Natural Language as infrastrucure details, adding the possibility to extend new behaviours
- UITableViewDiffableDataSource
- Child View Controllers (Plugin like)
- Dark Mode
- HTTP requests
- Error Handling
- CI using GitHub Actions
- Swift Package Manager
Third-party dependencies
- Kingfisher
Architecture Diagram
