A microservice built with FastAPI that analyzes resumes (PDF/DOCX) and extracts skills. This project demonstrates modern backend practices and applies the 12-Factor App principles.
- 📄 Upload PDF or DOCX resumes
- 🧠 Analyze resume content to extract:
- Detected skills
- Word/sentence count
- 🔄 Background processing using FastAPI’s
BackgroundTasks - ⚡ Async endpoints and DB operations
- 🧪 Pytest-based test coverage
- 🐳 Dockerized with optional Docker Compose
- 📋 CI/CD with GitHub Actions
- ✅ Clean architecture using FastAPI routers & dependencies
- 🧾 Follows 12-Factor principles
resume-analyzer-fastapi/
│
├── app/
│ ├── core/ # Config, logging, dependencies
│ ├── services/ # Business logic: parsing, analysis
│ ├── models/ # Pydantic and ORM models
│ ├── db/ # DB session and setup
│ └── main.py # FastAPI entry point
│
├── tests/ # Pytest test cases
├── .env # Environment variables
├── Dockerfile
├── docker-compose.yml
├── requirements.txt
├── .github/workflows/ # GitHub Actions
└── README.md
- Python 3.10+
- Docker (for containerized setup)
# 1. Clone the repo
git clone https://github.com/kar137/Resume-Analyzer-FastAPI.git
cd Resume-Analyzer-FastAPI
# 2. Create virtual environment
python -m venv venv
source venv/bin/activate # or venv\Scripts\activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Set environment variables
cp .env.example env
# 5. Run the app
uvicorn app.main:app --reload# Build and run using Docker Compose
docker-compose up --buildpytest| Method | Endpoint | Description |
|---|---|---|
| POST | /upload/ |
Upload a resume for analysis |
| GET | /result/{analysis_id} |
Fetch analyzed data by ID |
Open Swagger Docs at:
http://localhost:8000/docs
✅ Dependency Injection
✅ Background Tasks
✅ Pydantic Settings & Models
✅ Routers
✅ Custom Exceptions
✅ Middleware
✅ Async DB Calls
✅ Event Handlers (startup, shutdown)
| Principle | Implementation |
|---|---|
| Config | .env + pydantic.BaseSettings |
| Dependencies | Defined in requirements.txt |
| Backing services | Docker Compose |
| Dev/prod parity | Docker enables consistent environments |
| Logs | Configurable logging using Python logging module |
| Admin processes | CLI scripts or FastAPI endpoints (e.g., DB init, cache clear) |
None