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add workflows, improve README and pyproject.toml
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‎.github/workflows/python-package.yaml‎

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name: Python package
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on:
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push:
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branches: [ "main" ]
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pull_request:
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branches: [ "main" ]
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jobs:
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build:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: ["3.10", "3.11", "3.12"]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v3
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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python -m pip install flake8 pytest black isort
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if [ -f pyproject.toml ]; then
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pip install .[dev]
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fi
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- name: Lint with flake8
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run: |
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# Run flake8 and fail the build if there are any issues
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flake8 . --count --max-complexity=10 --max-line-length=88 --statistics
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- name: Lint with black
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run: |
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black --check .
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- name: Lint with isort
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run: |
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isort . --check-only
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- name: Test with pytest
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run: |
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pytest

‎.github/workflows/python-publish.yaml‎

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name: Upload Python Package
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on:
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release:
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types: [published]
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permissions:
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contents: read
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jobs:
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release-build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: "3.x"
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- name: Build release distributions
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run: |
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python -m pip install build
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python -m build
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- name: Upload distributions
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uses: actions/upload-artifact@v4
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with:
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name: release-dists
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path: dist/
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pypi-publish:
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runs-on: ubuntu-latest
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needs:
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- release-build
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permissions:
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id-token: write
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environment:
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name: pypi
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steps:
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- name: Retrieve release distributions
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uses: actions/download-artifact@v4
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with:
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name: release-dists
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path: dist/
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- name: Publish release distributions to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1
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with:
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packages-dir: dist/
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env:
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TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
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TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
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conda-publish:
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runs-on: ubuntu-latest
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needs:
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- release-build
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steps:
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- name: Install conda-build
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run: |
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sudo apt-get update
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sudo apt-get install -y conda
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conda install conda-build anaconda-client
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- name: Retrieve release distributions
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uses: actions/download-artifact@v4
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with:
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name: release-dists
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path: dist/
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- name: Build Conda package
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run: |
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conda-build .
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- name: Upload Conda package
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run: |
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anaconda login --username ${{ secrets.ANACONDA_USERNAME }} --password ${{ secrets.ANACONDA_PASSWORD }}
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anaconda upload /path/to/your/conda/package.tar.bz2

‎README.md‎

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# kissbt
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`kissbt` (Keep It Simple Stupid Backtesting) is a Python library designed for backtesting trading strategies with simplicity and ease of use in mind. The library provides essential components for creating, running, and analyzing trading strategies.
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**kissbt**, the `keep it simple` backtesting framework, is a lightweight and user-friendly Python framework for backtesting trading strategies. It focuses on simplicity, performance, and ease of extensibility while providing essential tools for effective backtesting.
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## Why kissbt?
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- **🚀 Lightweight** – Minimal dependencies ensure fast installation and execution.
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- **📖 Simple API** – Lowers the barrier for traders new to backtesting.
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- **🔌 Extensible** – Modular architecture enables easy customization.
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- **📊 Essential Features** – Includes tools for data handling, strategy implementation, and performance evaluation.
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## Features
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- **Modular Design**: The library is composed of several modules, each handling a specific aspect of the backtesting process.
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- **Strategy Implementation**: Easily implement custom trading strategies by extending the `Strategy` class.
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- **Broker Simulation**: Simulate trading with the `Broker` class, which manages orders, positions, and cash.
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- **Performance Analysis**: Analyze trading performance with the `Analyzer` class, which calculates key metrics like total return, Sharpe ratio, and drawdown.
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- **Data Handling**: Efficiently handle and preprocess market data using `pandas`.
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- **Visualization**: Plot equity curves and drawdowns to visualize strategy performance.
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✔️ Object-oriented design for intuitive strategy development
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✔️ Fast execution, even for large universes
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✔️ Supports long and short positions
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✔️ Built-in trade execution, position tracking, and P&L calculation
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✔️ Performance analysis with key trading metrics
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✔️ Backtesting with historical market data
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✔️ Modular components (Strategy, Broker, Engine, Analyzer)
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## Installation
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To install `kissbt`, clone the repository and install the dependencies:
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You can install `kissbt` using either `pip` or `conda`.
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### Using pip
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To install `kissbt` via `pip`, run the following command:
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```sh
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pip install kissbt
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```
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### Using conda
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To install `kissbt` via `conda`, run the following command:
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```bash
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git clone https://github.com/FinBlobs/kissbt.git
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cd kissbt
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pip install -r requirements.txt
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```sh
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conda install kissbt
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```
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## Usage
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from kissbt.entities import Order, OrderType
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class MyStrategy(Strategy):
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def generate_orders(self, current_data, current_datetime, previous_data=None, previous_datetime=None):
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def generate_orders(self, current_data, current_datetime):
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# Example: Buy if the close price is above the 128-day SMA
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for ticker in current_data.index.get_level_values('ticker').unique():
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close_price = current_data.loc[(current_datetime, ticker), 'close']
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sma_128 = current_data.loc[(current_datetime, ticker), 'sma_128']
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for ticker in current_data.index:
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close_price = current_data.loc[ticker, "close"]
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sma_128 = current_data.loc[ticker, "sma_128"]
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if close_price > sma_128:
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order = Order(ticker=ticker, size=10, order_type=OrderType.OPEN)
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self.broker.open_orders.append(order)
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self._broker.place_order(order)
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```
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### 2. Set Up the Broker
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```python
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from kissbt.broker import Broker
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broker = Broker(start_capital=100000, fees=0.001, tax_rate=0.2)
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broker = Broker(start_capital=100000, fees=0.001)
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```
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### 3. Run the Backtest
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## Contributing
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Contributions are welcome! Please feel free to submit a Pull Request.
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We welcome contributions! If you have ideas, bug fixes, or feature requests, feel free to open an issue or submit a pull request.
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## Contact
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‎pyproject.toml‎

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[project]
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name = "kissbt"
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version = "0.1.0"
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description = "A brief description of the project."
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description = "The keep it simple backtesting framework for Python."
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readme = "README.md"
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authors = [
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{ name = "Adrian Hasse", email = "adrian.hasse@finblobs.com" }
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]
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maintainers = [
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{ name = "Adrian Hasse", email = "adrian.hasse@finblobs.com" }
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]
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license = { file = "LICENSE" }
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classifiers = [
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: Apache Software License",
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"Operating System :: OS Independent"
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]
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dependencies = ["pandas"]
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dependencies = [
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"numpy>=2.0.0",
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"pandas>=2.0.0"
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]
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requires-python = ">=3.10"
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[project.optional-dependencies]
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dev = [
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"yfinance"
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]
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[project.urls]
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homepage = "https://github.com/FinBlobs/kissbt"
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bug-tracker = "https://github.com/FinBlobs/kissbt/issues"

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