# candlestick-patterns

This app creates a dashboard using [Dash](https://github.com/plotly/dash) to visualize and backtest candlestick patterns. 

* Supports [Yahoo! Finance](https://github.com/ranaroussi/yfinance) tickers
* Supports [TA-Lib](https://github.com/mrjbq7/ta-lib) candlestick patterns
* Allows to choose entry and exit patterns, and override candle settings
* Allows to specify signals manually
* Performs backtesting on selected signals using [vectorbt](https://github.com/polakowo/vectorbt)
* Visualizes OHLCV, signals, orders, trades and portfolio value using [Plotly](https://github.com/plotly/plotly.py)
* Displays key performance metrics such as Sharpe ratio
* Compares main strategy to holding and trading randomly
* Responsive design using [Dash Bootstrap Components](https://github.com/facultyai/dash-bootstrap-components)

## How to run the app

### Using Docker

Build the Docker image and run the container:

```bash
docker build -t candlestick-patterns . 
docker run -p 8050:8050 -e HOST='0.0.0.0' candlestick-patterns
```

Visit [http://127.0.0.1:8050/](http://127.0.0.1:8050/)

Note: Compiling for the first time may take a while.

### Using virtual environment

To get started, first clone this repo:

```bash
git clone https://github.com/polakowo/vectorbt.git
cd vectorbt/apps/candlestick-patterns
```

Create and activate a conda env:

```bash
conda create -n candlestick-patterns python=3.7.6
conda activate candlestick-patterns
```

Or a venv (make sure your Python is 3.6+):

```bash
python3 -m venv venv
source venv/bin/activate  # Unix
venv\Scripts\activate  # Windows
```

Install the requirements:

```bash
pip install -r requirements.txt
```

In case of errors related to TA-Lib, see [Troubleshooting](https://github.com/mrjbq7/ta-lib#troubleshooting).

Run the app:

```bash
python app.py
```

Visit [http://127.0.0.1:8050/](http://127.0.0.1:8050/)

## Screenshot

![screenshot.png](https://raw.githubusercontent.com/polakowo/vectorbt/master/apps/candlestick-patterns/screenshot.png)