https://github.com/shubhs27/stock-analyzer
A Django-based web application for visualizing stock market data with interactive candlestick charts and volume analysis.
https://github.com/shubhs27/stock-analyzer
aws-ec2 django docker nginx plotly postgresql stock-analysis
Last synced: 3 months ago
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A Django-based web application for visualizing stock market data with interactive candlestick charts and volume analysis.
- Host: GitHub
- URL: https://github.com/shubhs27/stock-analyzer
- Owner: shubhs27
- License: mit
- Created: 2025-06-11T10:25:20.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-03T13:21:04.000Z (11 months ago)
- Last Synced: 2025-08-15T04:19:06.339Z (11 months ago)
- Topics: aws-ec2, django, docker, nginx, plotly, postgresql, stock-analysis
- Language: Python
- Homepage:
- Size: 1.2 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Stock Market Analyzer
A Django-based web application for visualizing stock market data with interactive candlestick charts and volume analysis. Built with PostgreSQL database backend and containerized with Docker.
## Features
- **Interactive Candlestick Charts**: Professional-grade OHLC (Open, High, Low, Close) visualization using Plotly.js
- **Volume Analysis**: Color-coded volume bars showing market sentiment
- **Multiple Time Aggregations**: View data in daily, weekly, or monthly intervals
- **CSV Data Import**: Bulk import stock data from CSV files
- **Data Export**: Download filtered data as CSV
- **Responsive Design**: Works seamlessly across desktop and mobile devices
- **Docker Support**: Easy deployment with Docker and Docker Compose
## Screenshots
### Home Page
### Monthly Analysis
### Weekly Aggregation
### Daily View
## Technology Stack
- **Backend**: Django 4.x, Python 3.x
- **Database**: PostgreSQL
- **Frontend**: HTML5, CSS3, JavaScript
- **Visualization**: Plotly.js
- **Containerization**: Docker, Docker Compose
- **Web Server**: Nginx (production)
## Project Structure
```
STOCK_VIEWER/
├── docker-compose.yml # Docker orchestration
├── Dockerfile # Django app container
├── nginx.conf # Nginx configuration
├── requirements.txt # Python dependencies
├── manage.py # Django management script
├── load_data.py # CSV import script
├── stock_viewer/ # Django project settings
│ ├── settings.py
│ ├── urls.py
│ └── wsgi.py
├── stocks/ # Main Django app
│ ├── models.py # Database models
│ ├── views.py # View controllers
│ ├── urls.py # URL routing
│ └── migrations/ # Database migrations
├── templates/stocks/ # HTML templates
│ └── index.html
├── static/ # Static assets
│ ├── css/style.css
│ ├── js/script.js
│ └── images/ # Screenshots
├── StocksData/ # CSV data directory
└── .env # Environment variables
```
## Quick Start
### Prerequisites
- Docker and Docker Compose
- Python 3.8+ (for local development)
- Git
### 1. Clone the Repository
```bash
git clone
cd stock_viewer
```
### 2. Environment Setup
Create a `.env` file in the root directory:
```env
# Database Configuration
DB_NAME=stock_db
DB_USER=stock_user
DB_PASSWORD=your_secure_password
DB_HOST=db
DB_PORT=5432
# Django Configuration
SECRET_KEY=your-super-secret-django-key-here
DEBUG=True
```
### 3. Docker Deployment
```bash
# Build and start all services
docker-compose up --build
# Run in background
docker-compose up -d --build
```
The application will be available at `http://localhost:8080`
### 4. Import Stock Data
Place your CSV files in the `StocksData/` directory with the following format:
```csv
Date,Open,High,Low,Close/Last,Volume
01/03/2023,$150.20,$155.40,$149.80,$154.90,1250000
```
Run the data import script:
```bash
# Using Docker
docker-compose exec web python load_data.py
# Or locally
python load_data.py
```
## Development Setup
### Local Development
1. **Create Virtual Environment**:
```bash
python -m venv venv
source venv/bin/activate # Linux/Mac
# or
venv\Scripts\activate # Windows
```
2. **Install Dependencies**:
```bash
pip install -r requirements.txt
```
3. **Setup Database**:
```bash
# Make sure PostgreSQL is running locally
python manage.py makemigrations
python manage.py migrate
```
4. **Run Development Server**:
```bash
python manage.py runserver
```
## API Endpoints
### Chart Data API
- **URL**: `/api/chart-data/`
- **Method**: POST
- **Content-Type**: `application/json`
**Request Body**:
```json
{
"company_id": 1,
"start_date": "2023-01-01",
"end_date": "2023-12-31",
"aggregation": "daily"
}
```
**Response**:
```json
{
"chart_data": {
"dates": ["2023-01-01", "2023-01-02"],
"opens": [150.2, 154.9],
"highs": [155.4, 158.3],
"lows": [149.8, 153.2],
"closes": [154.9, 157.8],
"volumes": [1250000, 1100000]
},
"data_points": 2,
"company_name": "AAPL",
"aggregation": "daily"
}
```
## Database Schema
### Companies Table
```sql
CREATE TABLE stocks_company (
id SERIAL PRIMARY KEY,
name VARCHAR(100) UNIQUE,
symbol VARCHAR(10) UNIQUE,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
```
### Stock Data Table
```sql
CREATE TABLE ohlc_data (
id SERIAL PRIMARY KEY,
company_symbol VARCHAR(10),
date DATE,
open DECIMAL(10,2),
high DECIMAL(10,2),
low DECIMAL(10,2),
close DECIMAL(10,2),
volume BIGINT,
file_source VARCHAR(50),
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
UNIQUE(company_symbol, date)
);
```
## Data Import Format
Your CSV files should follow this format:
```csv
Date,Open,High,Low,Close/Last,Volume
01/03/2023,$150.20,$155.40,$149.80,$154.90,1250000
01/04/2023,$154.90,$158.30,$153.20,$157.80,1100000
```
**Supported formats**:
- Date format: `MM/DD/YYYY`
- Price columns can include `$` symbol (automatically cleaned)
- File naming: `COMPANY_SYMBOL.csv` (e.g., `AAPL.csv`)
### Docker Services
- **web**: Django application server
- **db**: PostgreSQL database
- **nginx**: Reverse proxy and static file server
## Troubleshooting
### Common Issues
1. **Database Connection Error**:
- Ensure PostgreSQL is running
- Check database credentials in `.env`
- Verify network connectivity between containers
2. **CSV Import Fails**:
- Check CSV format matches expected structure
- Ensure date format is `MM/DD/YYYY`
- Verify file permissions
3. **Chart Not Loading**:
- Check browser console for JavaScript errors
- Ensure API endpoint is accessible
- Verify data exists for selected date range
### Logs
```bash
# View application logs
docker-compose logs web
# View database logs
docker-compose logs db
# Follow logs in real-time
docker-compose logs -f
```
## Future Enhancements
- **Real-time Data Integration**: Live market data feeds with WebSocket support for automatic price updates and streaming quotes
- **Technical Indicators**: RSI, MACD, Bollinger Bands, moving averages, and other momentum/volatility indicators
- **Portfolio Management Features**: Track multiple portfolios, transactions, performance analytics, and asset allocation
- **Comparison Tools**: Side-by-side chart comparisons, peer analysis, and performance benchmarking
- **User Authentication**: Secure login, personal dashboards, watchlists, and role-based access control
- **Machine Learning Capabilities**: Price forecasting, pattern recognition, sentiment analysis, and automated trading signals
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.