Stock Predictor API

A FastAPI backend for stock price prediction using machine learning. Users can upload historical stock data, receive price predictions, analyze trends, and visualize historical performance.

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Features

• JWT authentication with bcrypt password hashing
• Upload historical stock data via CSV
• Stock price prediction using Linear Regression with moving averages (SMA_20, SMA_50)
• Historical trend analysis and data visualization
• User feedback system

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Tech Stack

• Backend: FastAPI, SQLAlchemy 2.0, Pydantic v2
• ML: scikit-learn, pandas
• Database: PostgreSQL
• Auth: JWT (PyJWT), bcrypt
• Migrations: Alembic
• Package manager: uv
• Containerization: Docker, Docker Compose

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Project Structure

stock_predictor/
├── auth/               # JWT token generation and verification
├── config/             # App settings via pydantic-settings
├── database/           # SQLAlchemy engine, session, Base
├── dependencies/       # FastAPI dependencies (get_db, get_current_user)
├── feedback/           # Feedback domain (models, schemas, crud, service, router)
├── stock/              # Stock domain (models, schemas, crud, service, router)
└── user/               # User domain (models, schemas, crud, service, router)
main.py
alembic/
tests/
Dockerfile
docker-compose.yml

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Getting Started

Prerequisites

• Docker and Docker Compose installed
• uv installed (pip install uv)

Environment Variables

Create a .env file in the root directory based on .env.example:

SECRET_KEY=your-secret-key-here
DATABASE_URL=postgresql://user:password@localhost:5432/stock_predictor
POSTGRES_USER=your-postgres-user
POSTGRES_PASSWORD=your-postgres-password

Run with Docker

docker compose up --build

This will:

1. Start PostgreSQL and wait until healthy
2. Run Alembic migrations
3. Start the FastAPI server on http://localhost:8000

Run locally

uv sync
alembic upgrade head
uv run main.py

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API Endpoints

User

Method	Endpoint	Auth	Description
POST	/user/signup	No	Register a new user
POST	/user/login	No	Login and receive JWT token
GET	/user/profile	Yes	Get current user profile
PUT	/user/profile	Yes	Update current user profile

Stock

Method	Endpoint	Auth	Description
POST	/stock/data	Yes	Upload historical stock data (CSV)
GET	/stock/predict	Yes	Get price predictions
GET	/stock/trends	Yes	Get historical trend analysis
GET	/stock/visualize	Yes	Get data for visualization

Feedback

Method	Endpoint	Auth	Description
POST	/feedback	Yes	Submit prediction feedback

Authentication

Protected endpoints require a Bearer token in the Authorization header:

Authorization: Bearer <access_token>

CSV Format

The stock data CSV must follow the OHLCV standard:

symbol,date_stamp,time_stamp,open,high,low,close,volume
AAPL,2024-01-01,14:30:00,185.50,186.20,184.90,185.80,52341000

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Running Tests

uv run pytest tests/

Tests use an in-memory SQLite database — no PostgreSQL required.

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Migrations

# Generate a new migration after model changes
alembic revision --autogenerate -m "description of change"

# Apply migrations
alembic upgrade head

# Revert last migration
alembic downgrade -1

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API Documentation

Interactive API docs available at:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc