Stock Viewer

A Python-based stock viewer built with lightweight_charts, yfinance, pandas, pandas_ta, and ib_insync for displaying historical and live-ish market data, with future plans for broker-connected trade execution.

Overview

This project is a stock visualization tool designed to load and display market data from multiple sources:

• yfinance for historical and delayed market data
• Interactive Brokers through ib_insync for broker-connected market data
• local CSV files for testing and development

The current focus is on building a reliable charting and data display workflow. The long-term goal is to expand the project into a more complete trading application that can eventually support trade execution.

Features

• Display OHLCV stock data in lightweight_charts
• Load historical stock data from yfinance
• Add technical indicators such as SMA with pandas_ta
• Load chart data from CSV files
• Connect to Interactive Brokers for broker-based data
• Work toward live or live-ish chart updates on a 1-minute interval
• Provide a foundation for future automated or manual trade execution

Project Goals

Current goals

• Build a clean stock viewer for charting market data
• Support multiple data sources
• Make chart updates work reliably for minute-based data
• Improve formatting and compatibility between data providers and chart input requirements

Future goals

• Add real-time broker-connected updates
• Add indicator overlays and multiple chart tools
• Support order entry and execution through a broker
• Build a more complete trading dashboard

Technologies Used

• Python
• pandas
• pandas_ta
• yfinance
• lightweight_charts
• ib_insync

Example Use Cases

1. View historical data from yfinance

Load stock data such as MSFT and display it as a candlestick chart.

2. Overlay indicators

Calculate and display indicators such as a 20-period simple moving average.

3. Load from CSV

Use local OHLCV data for testing chart behavior and formatting.

4. Connect to Interactive Brokers

Request broker market data and historical bars, then update the chart dynamically.

Repository Structure

You can organize the repo like this:

stock-viewer/
│
├── live/
│   ├── live_chart.py
│   └── ib_live_chart.py
│
├── examples/
│   ├── yf_chart.py
│   ├── sma_chart.py
│   └── csv_chart.py
│
├── data/
│   └── ohlcv.csv
│
├── requirements.txt
└── README.md