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Python backtesting framework for trading strategies. Data feeds, brokers, analyzers, and live trading support. Strategy development with commission models, slippage, and signal-based execution.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/mkurman/zorai --skill backtrader命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | backtrader |
| description | Python backtesting framework for trading strategies. Data feeds, brokers, analyzers, and live trading support. Strategy development with commission models, slippage, and signal-based execution. |
| tags | ["backtesting","trading","strategy","backtest","quant-finance","python","zorai"] |
Backtrader is a Python backtesting framework for trading strategies. Supports multiple data feeds, live trading, commission/slippage models, custom analyzers, and visualization. Well-suited for equity, futures, and crypto strategy development.
uv pip install backtrader
import backtrader as bt
class SmaCross(bt.Strategy):
params = dict(short=10, long=30)
def __init__(self):
sma_short = bt.ind.SMA(self.data.close, period=self.params.short)
sma_long = bt.ind.SMA(self.data.close, period=self.params.long)
self.crossover = bt.ind.CrossOver(sma_short, sma_long)
def next(self):
if self.crossover > 0:
self.buy()
elif self.crossover < 0:
self.sell()
cerebro = bt.Cerebro()
data = bt.feeds.YahooFinanceData(dataname="AAPL", fromdate="2022-01-01", todate="2023-01-01")
cerebro.adddata(data)
cerebro.addstrategy(SmaCross)
cerebro.broker.setcash(10000.0)
print(f"Final value: ${cerebro.run()[0]:.2f}")
cerebro.plot()