backtest-manager-vscode

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backtest-manager-vscode

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Backtest manager in VSCode Extension

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# Backtest Manager

Backtest Manager is a powerful VSCode extension that streamlines algorithmic trading strategy development, making backtesting both simple and efficient.

![VSCode Badge](https://img.shields.io/badge/Vscode-Marketplace-blue)
![Backtest Engine](https://img.shields.io/badge/Engine-backtrader-green)
![Backtest Engine](https://img.shields.io/badge/Engine-vectorbt-green)
</div>

## ✅ Why Use Backtest Manager?

Developing trading strategies can be complex and time-consuming. Backtest Manager offers:
- **Streamlined Development** – Direct integration with your IDE and engine lets you focus on strategy logic, eliminating setup complexities.
- **Real-time Analysis** – Get instant visualization of results and quickly iterate parameters with comprehensive performance metrics.
- **AI-Enhanced Workflow** – Accelerate development using advanced AI assistants (Copilot, Cursor, Roo, Cline).

## 🌟 Key Features

|   |   |   |
|:-:|:-:|:-:|
| ![setting-view](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/backtest-setting.png) | ![result-view](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/result-analysis.png) | ![dataset-download](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/dataset-download.png) |
| Strategy Settings | Result Analysis | Dataset Management |

- **Strategy & Backtest Management**: Build, organize, and keep your backtest projects tidy in VSCode.
- **Quick Parameter Tweaks**: Change settings and rerun tests easily.
- **Visual Analysis**: Instantly view results with clear charts and stats.
- **Dataset Download**: Easily fetch datasets from any exchange and timeframe.

## 🚀 Currently Supported Engines

- [Backtrader](https://www.backtrader.com/)
- [VectorBT](https://vectorbt.dev/)
- Any Python-based Backtest Engines (choose your favorite)

Coming Soon...
- [Nautilus Trader](https://nautilustrader.io/), [LEAN Engine (QuantConnect)](https://www.quantconnect.com/), Language support beyond Python

## 🚦 Getting Started

### 📋 Installation Requirements

- Visual Studio Code 1.98.0 or higher
- Python 3.8+
- Backtest libraries (Choose)

```bash
# backtrader
pip install backtrader

# vectorBT
pip install vectorbt
```

### 💻 Extension Installation

1. Search for and install the [Backtest Manager](https://marketplace.visualstudio.com/) extension in the VSCode marketplace.
2. Restart VSCode (recommended).

## 📚 How to Use

### ✍️ Writing Strategies

Backtest Manager provides a basic template, and you can write your own strategies, even let AI write instead of you! Let your trading ideas flow!

<details>
<summary>Backtrader Example</summary>

```python
import backtrader as bt
import os

class SMACrossOverStrategy(bt.Strategy):
    params = (
        ('fastPeriod', int(os.environ['fast'])),
        ('slowPeriod', int(os.environ['slow'])),
        ('stopLoss', 2),
        ('takeProfit', 5)
    )
    
    def __init__(self):
        self.fast_ma = bt.indicators.SimpleMovingAverage(
            self.data.close, 
            period=self.params.fastPeriod
        )
        self.slow_ma = bt.indicators.SimpleMovingAverage(
            self.data.close, 
            period=self.params.slowPeriod
        )
        
        self.crossover = bt.indicators.CrossOver(self.fast_ma, self.slow_ma)
        
        self.entry_price = None
        self.stop_loss = None
        self.take_profit = None
        
    def next(self):
        if not self.position:
            if self.crossover > 0:
                close = self.data.close[0]
                self.buy()
                self.entry_price = close
                
                self.stop_loss = close * (1 - self.params.stopLoss / 100)
                self.take_profit = close * (1 + self.params.takeProfit / 100)
        else:
            close = self.data.close[0]
        
            if close <= self.stop_loss or close >= self.take_profit:
                self.close()
                self.entry_price = None
                self.stop_loss = None
                self.take_profit = None
                return
            
            if self.crossover < 0:
                self.close()
                self.entry_price = None
                self.stop_loss = None
                self.take_profit = None

def cerebro_init(cerebro: bt.Cerebro):
    cerebro.addsizer(bt.sizers.PercentSizer, percents=95)

# No driver code (e.g. cerebro.run()) needed
# Backtrader Documentation: https://www.backtrader.com/docu/quickstart/quickstart/
```
Each project must include a `cerebro_init` function. This lets the extension handle data loading and configuration automatically before running your backtest.

</details>

<details>
<summary>VectorBT Example</summary>

```python
import vectorbt as vbt

# Build portfolio args 
def portfolio_init(close) -> dict:
    portfolio_kwargs = {}
    
    fast_ma = vbt.MA.run(close, 10)
    slow_ma = vbt.MA.run(close, 50)

portfolio_kwargs['close'] = close
    portfolio_kwargs['entries'] = fast_ma.ma_crossed_above(slow_ma)
    portfolio_kwargs['exits'] = fast_ma.ma_crossed_below(slow_ma)
    
    return portfolio_kwargs

# No driver code (e.g. vbt.Portfolio.from_signals()) needed
# VectorBT Documentation: https://vectorbt.dev/
```
Each project must include a `portfolio_init` function. The extension uses this to load data, set parameters, and run your backtest automatically.

</details>

<details>
<summary>Custom Engine Example</summary>

```python
# Write backtesting code with your custom engine here.
# Don't forget to print your backtest results so that Backtest Manager can capture them.

print("t: {
    'ref': 0, 
    'datetime': "2024-05-30T14:00:00+00:00", 
    'price': 10202.0, 
    'size': 2, 
    'value': 20404.0, 
    'commission': 20.4, 
    'side': 'long'
}")

print("t: {
    'ref': 0,
    'datetime': "2024-05-31T00:00:00+00:00",
    'price': 10302,
    'size': 2,
    'pnl': 200.0,
    'pnlcomm': 179.6,
    'commission': 20.4,
    'hold_bars': 10
}")

print("e: { 
    'datetime': "2024-05-30T14:00:00+00:00", 
    'value': 3000000 
}")

```
</details>

### 🆕 Create a New Project
Start a new backtest project. Choose your favourite backtest engine.

|   |
|:-:|
| ![create-project](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/create-project.png) |
| Create New Project |

### 📥 Download Dataset
Easily download historical data for your backtests with just a few clicks.

|   |   |
|:-:|:-:|
| ![dataset-tree](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/dataset-tree.png) | ![dataset-download](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/dataset-download.png) |
| Dataset Organization | Dataset Download Interface |

### ⚙️ Setting Parameter and Running a Backtest
Ready, Set, Go!

|   |
|:-:|
| ![setting-view](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/backtest-setting.png) |
| Parameter Configuration |

### 📊 Result Analysis
Analyze your strategy's performance with comprehensive analytics:
- Equity curve graph – visualize your profits
- Performance metrics (total return, Sharpe ratio, max drawdown, win rate, etc.)
- Trade history (time, price, size, profit, etc.)

|   |
|:-:|
| ![result-view](https://raw.githubusercontent.com/woung717/backtest-manager-vscode/main/resource/result-analysis.png) |
| Performance Analytics |

### 🐞 Debugging Strategy
You can enable verbose output for your backtest scripts and choose whether to automatically delete completed backtest scripts in the extension settings.

## 📜 License

Distributed under the MIT License.

## 🤝 Contributing

Have ideas to make this even better? Issues and pull requests are always welcome! Please check the issue tracker before contributing.

backtest-manager-vscode

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