Welcome to the fifth installment in our series on building a modern web application for Raleigh AI Solutions! In this video, we take a deep dive into building a robust testing infrastructure to ensure our application is reliable, maintainable, and bug-free.
What You'll Learn in This Video:
Setting up Vitest for comprehensive testing with TypeScript and React.
Configuring an isolated test database for reliable, independent tests.
Creating mock utilities for external services like Clerk and OpenAI.
Writing and running unit and integration tests for core features.
Implementing a debug logging system to make troubleshooting efficient.
Testing is a critical part of any application development process, and this video aims to demystify the complexities of creating a reliable testing setup. We cover everything from installing the necessary dependencies, configuring testing environments, and writing robust tests, to effectively using mocks and debug tools.
Resources & Links Mentioned in the Video:
Full GitHub Branch with Code for Video 5: GitHub - Raleigh AI Content (Video 5 Branch): github.com/thorski1/Raleigh-AI-Content/blob/video-5
Drizzle ORM Documentation: Drizzle ORM Docs: orm.drizzle.team
Vitest Documentation: Vitest Docs: vitest.dev
pgvector for Embedding Storage: pgvector GitHub: github.com/pgvector/pgvector
Key Highlights:
Vitest Configuration: We configure Vitest to work seamlessly with TypeScript, set up plugins to handle React components, and define the proper environment setup.
Database Helper and Test Setup: Learn to manage the test database lifecycle with helper files for database seeding, resetting, and teardown to keep tests isolated.
Mocking External Services: We cover the importance of creating mock files for services like Clerk, OpenAI, and our database, which allows for isolated and reliable testing.
Integration Testing: Dive into writing integration tests for authentication, document management, and content handling with a focus on edge cases.
Debug Logging System: Implement a debugging utility to quickly identify and troubleshoot test failures.
Get the Full Source Code:
Check out the GitHub repository linked above to access all the code shown in the video. You’ll find the configurations, helper files, mock implementations, and test suites we've discussed.
About the Series:
This series covers the full journey of building a modern web application, starting from database setup, integration of AI services, to comprehensive testing, and beyond. If you've missed any part of the series, make sure to check out our playlist: Building Modern Web Apps for Raleigh AI Solutions: th-cam.com/play/PLm8mpUfGYwyE_xPjPyDiVxd9vmKbg6pDA.html.
Next Video in the Series:
In the next video, we’ll be moving on to building our RAG (Retrieval-Augmented Generation) engine. This system will help us create dynamic, relevant content for users by combining information retrieval and content generation techniques. Make sure to subscribe and hit the notification bell so you don't miss it!
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