https://github.com/devraider/trading-app
This Django-based application was developed as part of a take-home assignment for NCH Invest. It processes trade data from Excel files, validates, and stores it in the database.
https://github.com/devraider/trading-app
Last synced: 2 months ago
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This Django-based application was developed as part of a take-home assignment for NCH Invest. It processes trade data from Excel files, validates, and stores it in the database.
- Host: GitHub
- URL: https://github.com/devraider/trading-app
- Owner: devraider
- Created: 2024-12-13T16:00:02.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-29T22:07:56.000Z (over 1 year ago)
- Last Synced: 2026-01-03T20:30:08.081Z (6 months ago)
- Language: Python
- Homepage:
- Size: 564 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Financial Web Application
## Motivation
This project was developed as a take-home assignment for the **NCH Invest** interview.
## Tech Stack
- **Backend**: Python, Django
- **Database**: PostgreSQL
- **Frontend**: TailwindCSS
- **Data Integration**: Yahoo Finance API (`yfinance`) - **_(To be implemented)_**
- **Containerization**: Docker, Docker Compose
---
## Features
### Implemented Features
1. **Logging**
- Basic logging set up to track application activity.
- Error logs to capture issues with trades or API interactions.
2. **Frontend**:
- Responsive design using TailwindCSS.
3. **Trades Processing**:
- Import Excel-based trades files.
- Validate trade data for accuracy and consistency.
- Calculate daily net positions based on imported trades.
- Store trades and calculated positions in the database.
4. **P&L Processing**:
- Import Excel-based trades files.
- Validate trade data for accuracy and consistency.
- Differentiate between realized and unrealized P&L.
- Compute daily Profit & Loss for each position.
## Demo & Walkthrough
### Trade Processing
1.
2.
3.
### P&L Processing
1.
2.
3.
---
## Installation Guide
### Prerequisites
- Docker and Docker Compose installed on your machine.
- Python 3.12+ (if running outside Docker).
- PostgreSQL 12+.
### Steps
1. **Clone the Repository**:
```bash
git clone
cd trading_app
```
2. **Set Up Environment Variables**:
Create a `.env` file in the root directory with the following:
```env
DEBUG=INFO
SECRET_KEY=
POSTGRES_DB=
POSTGRES_USER=
POSTGRES_PASSWORD=
POSTGRES_HOST=
POSTGRES_PORT=5432
```
3. **Build and Start Docker Containers**:
```bash
docker compose up --build
```
4. **Access the Application**:
- Visit [http://localhost:8000](http://localhost:8000) in your browser.
---
## Project Structure
```
trading_app/
├── docker/
│ ├── Dockerfile
│ └── docker-compose.yml
├── samples/
│ ├── pnl
│ │ ├── trades_example.xlsx (file with formulas to guide development process)
│ │ └── pnl.xlsx (sample file for testing)
│ └── trading-processor
│ └── trading-processor
│ ├── trades_250_entries.xlsx
│ ├── trades_2000_entries.xlsx
│ └── trades_4_entries.xlsx
├── src/
│ ├── static/
│ │ └── uploads/
│ │ └── (uplded .xlsx file by the user)
│ ├── templates/
│ │ ├── base.html
│ │ ├── pnl.html
│ │ ├── trade_processor.html
│ │ └── welcome.html
│ ├── trading/
│ │ ├── models.py
│ │ ├── migrations/
│ │ │ └── (all migration after running makemigration command)
│ │ ├── repository/
│ │ │ ├── base_repo.py
│ │ │ ├── positions.py
│ │ │ └── tranzactions.py
│ │ └── tests/
│ │ ├── services/
│ │ │ ├── yahoo_finance.py
│ │ │ ├── trade_processor.py
│ │ │ └── pnl_processor.py
│ │ ├── views.py
│ │ ├── urls.py
│ │ ├── tools.py
│ │ ├── settings.py
│ │ ├── asgi.py
│ │ └── wsgi.py
│ └── manage.py
├── requirements.txt
├── .gitignore
└── README.md
```
---
## Requirements
#### Trades Processing
- Parse Excel trade files using `pandas`.
- Validate trade data (e.g., required fields, valid symbols).
- Store validated trades in the database.
- Calculate daily net positions (quantity × price × direction).
#### Data Fetching
- Use Yahoo Finance API to fetch stock OHLCV data.
- Incrementally update the database with new data.
- Handle API rate limiting and errors gracefully.
#### P&L Calculation
- Compute daily Profit & Loss for each position.
- Differentiate between realized and unrealized P&L.
#### Frontend
- Display key financial data with TailwindCSS:
- Current positions in a table.
- Daily P&L in an interactive chart.
---
## Testing
Tests must be implemented and adding step to run tests during deployment (`Dockerfile`)
---
## Acknowledgments
This application was developed as part of a take-home project for **NCH Invest**.