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kernc/backtesting.py

🔎 📈 🐍 💰 Backtest trading strategies in Python. observed · 2026-08-28

github.com/kernc/backtesting.py · homepage · Python · AGPL-3.0 (copyleft) observed · 2026-08-28

Health v2 · maintenance only

75/100

  • Activity 96
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2800
  • days_rel: n/a
  • days_push: 28
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

8893 stars · 1520 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Backtesting.py is a lightweight Python framework for backtesting trading strategies against historical candlestick data. It provides a small, clean Strategy/Backtest API, works with any technical indicator library, and produces interactive performance plots and statistics.

Use cases

  • backtest a trading strategy on historical OHLC data
  • test moving average crossover strategies in Python
  • evaluate strategy performance with stats like return and volatility
  • simulate forex, crypto, or stock strategies before live trading
  • plot interactive equity curves and trade markers
  • compare a strategy against buy-and-hold returns

When to choose

  • you want a fast, lightweight, well-documented backtesting library with a small API
  • you already work in Python with Pandas/NumPy and any TA library
  • you need interactive visualizations of backtest results
  • you backtest single-instrument, bar-based (vectorized/event-driven) strategies

When to avoid

  • you need live trading or broker integration - this library only backtests
  • you need multi-asset portfolio backtesting or complex order types
  • your project cannot comply with the AGPL-3.0 license
  • you need tick-level or high-frequency data simulation

Facets

framework · maturity active

trading simulation data-visualization benchmarking fintech data-science python cross-platform backtesting algorithmic-trading technical-analysis finance pandas bokeh trading python

2 sources

Member repositories

RepositoryRoleHealth v2
kernc/backtesting.pymain75

For agents

markdown · JSON · MCP: product_card(name="kernc/backtesting.py")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem