Spec driven development project created#23
Open
vishalnaik-25 wants to merge 1 commit intoautomationExamples:mainfrom
Open
Spec driven development project created#23vishalnaik-25 wants to merge 1 commit intoautomationExamples:mainfrom
vishalnaik-25 wants to merge 1 commit intoautomationExamples:mainfrom
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This project was built using a Spec-Driven Development approach where every feature was defined in the SPECS/ directory before implementation. The application is a backend-only Book Review API built with FastAPI, using in-memory storage to keep the setup simple and fully local.
Core features include book creation, adding reviews, automatic average rating calculation, and filtering via query parameters. A comprehensive test suite using pytest validates all workflows, edge cases, and error scenarios, with isolated in-memory state for deterministic results.
AI code generation tools were used to accelerate specification writing, implementation, testing, and refactoring while maintaining clean architecture and clear separation of concerns.
All tests pass, the application runs locally, and the project strictly follows the defined development rules.