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Search NYC subway routes and plan trips using a map
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LifestylePython · HTMLGitHub @FukamiRuiOnlineOwner unconfirmed
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Read the full README ↗A high-performance subway route search application using GTFS (General Transit Feed Specification) data for the New York City Metro system. Built with FastAPI, SQLAlchemy, and Sliding Window / Binary Search algorithms.
Hosted on Vercel (Python serverless function).
| Category | Technologies |
|---|---|
| Language | Python 3.14 |
| Backend Framework | FastAPI, Uvicorn, Gunicorn |
| Database & ORM | PostgreSQL, SQLite, SQLAlchemy (ORM) |
| Frontend | HTML5, CSS3, JavaScript |
| Testing & Quality | Pytest (Unit & Integration), Pytest-Cov |
| DevOps & CI/CD | Docker, Docker Compose, GitHub Actions |
This application processes NYC Subway GTFS data:
| Algorithm / Feature | Time Complexity | Space Complexity | Optimization Strategy |
|---|---|---|---|
| Direct Route Search | O(log N + M) | O(M) | Binary search (bisect_left) on cached departure times |
| Transfer Search (BFS) | O(V + E) | O(V) | BFS with visited-state pruning and maximum transfer depth |
| Nearest Station | O(N) | O(1) | Haversine distance over cached station coordinates |
.coveragerc)pytest and coverage checks on every Push and Pull Request. Stmts Miss Cover
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TOTAL 530 66 88%
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├── .github/
│ └── workflows/
│ └── python-app.yml # GitHub Actions CI Workflow
├── data/
│ └── gtfs/
│ ├── routes.txt
│ ├── stops.txt
│ ├── trips.txt
│ └── stop_times.txt
├── models.py # SQLAlchemy DB Models
├── database.py # Database Connection & Session Management
├── main.py # FastAPI entry point: /search_route, /check_stations, calculate_nearest_station
├── search.py # Core algorithms: direct search (binary search), transfer search (depth-bounded BFS), nearest station (Haversine)
├── test_api.py # Pytest Test Cases
├── .coveragerc # Coverage Exclusions Configuration
├── Dockerfile
├── docker-compose.yml
├── .dockerignore
└── requirements.txt
This is the beginning of the README. Read the rest at the original. Read the full README ↗