Open
Conversation
…ance criteria
- Fix: Move /transactions/summary endpoint before /{transaction_id} to prevent route matching issues
- Fix: Add test isolation by clearing storage between tests
- Fix: Update summary() to initialize all categories
- Improve: Add comprehensive docstrings to all functions and classes
- Update: Check off all completed acceptance criteria in feature spec
- Update: Refresh TODO.md with meaningful future proposals
- Add: Populate .gitignore with Python-specific patterns
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
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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 pull request introduces a complete backend application for automatic transaction categorization, following a spec-driven development approach. The implementation includes API endpoints for creating, listing, filtering, deleting, and summarizing financial transactions, with rule-based categorization logic and in-memory storage. The codebase is fully tested, documented, and reproducible locally. The most important changes are grouped below by theme.
Core Application Implementation
app/main.pywith endpoints for transaction creation, listing, filtering, deletion, and summary, leveraging rule-based categorization and in-memory storage.app/categorizer.pyfor keyword-based assignment to one of six categories.app/models.pyfor transaction data and input enforcement.app/storage.pyfor transaction CRUD and summary operations.Testing
tests/test_api.pycovering all API endpoints, input validation, and edge cases, ensuring high coverage and reliability.tests/test_categorizer.py.Documentation & Developer Experience
README.md.TESTING.mdand a ready-to-use Postman collection for API requests. [1] [2]SPECS/api-spec.mdand outlined feature scope and acceptance criteria inSPECS/feature-template.md. [1] [2]APPROACH.md.Project Hygiene
RULES.md,TODO.md) and added package markers for Python modules. [1] [2] [3] [4]Summary:
This PR delivers a fully spec-driven, AI-assisted backend for transaction categorization, with robust documentation, testing, and developer tooling for easy local setup and validation.