GitHub - kar137/Resume-Analyzer-FastAPI: microservice built with FastAPI to analyze resume

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.

👨‍💻 Tech Stack Used

🚀 Features

📄 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

📁 Project Structure

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

⚙️ Setup & Run

🔧 Prerequisites

Python 3.10+
Docker (for containerized setup)

🐍 Local Setup (Without Docker)

# 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

🐳 Docker Setup

# Build and run using Docker Compose
docker-compose up --build

🧪 Running Tests

📥 API Endpoints

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

🧪 FastAPI Concepts Used

✅ Dependency Injection
✅ Background Tasks
✅ Pydantic Settings & Models
✅ Routers
✅ Custom Exceptions
✅ Middleware
✅ Async DB Calls
✅ Event Handlers (startup, shutdown)

📦 12-Factor Implementation Highlights

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)