# quantopian/zipline

Zipline, a Pythonic Algorithmic Trading Library

Repository: https://github.com/quantopian/zipline
Canonical: https://ross.abutalabs.com/products/zipline
Homepage: https://www.zipline.io
Language: Python
License: Apache-2.0
License Family: permissive
Topics: quant, python, algorithmic-trading, zipline
Last push: 2024-02-13T08:02:51+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5066, "days_push": 932, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 20070, forks 5040 (observed 2026-08-28T04:11:29.621073+00:00)

## What it is
Zipline is a Pythonic, event-driven algorithmic trading library for backtesting strategies, originally built as the engine powering the Quantopian platform. It integrates with the PyData ecosystem (Pandas, NumPy, matplotlib, scikit-learn) and provides built-in statistics and historical data handling for strategy development.

## Use cases
- backtest a trading strategy in python
- event-driven backtesting engine for quant strategies
- test a moving average crossover strategy on historical data
- simulate algorithmic trading strategies with pandas data
- python library for quantitative finance research
- compute performance statistics for trading algorithms

## When to choose
- you want a mature, battle-tested Python backtester with PyData integration
- you are prototyping or researching trading strategies in Python
- you need built-in trading statistics like moving averages and regression within your algorithm

## When to avoid
- you need live trading with modern broker integrations out of the box
- you require support for recent Python versions, as the original project targets older Python (2.7-3.6)
- you want an actively developed project - consider maintained forks like zipline-reloaded

## Facets
- artifact type: library
- maturity: maintenance
- function: trading, simulation, data-science, benchmarking
- domain: fintech, data-science
- platform: python, windows
- tags: backtesting, algorithmic-trading, quant, event-driven, pandas, quantitative-finance, algorithms, python, linux, macos

## Member repositories
- quantopian/zipline (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:29.621073+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:59:21.773477+00:00, confidence not recorded.
  - readme: https://github.com/quantopian/zipline (fetched 2026-08-28T04:11:29.621073+00:00, sha b49a82a5acc1)
  - homepage: https://www.zipline.io (fetched 2026-08-29T07:57:52.346956+00:00, sha 00f8a40f0dc1)
  - site_page: https://www.zipline.io/about (fetched 2026-08-29T07:57:52.362740+00:00, sha 92aea5fa0d5c)
  - site_page: https://www.zipline.io/products/visitor-compliance (fetched 2026-08-29T07:57:52.356615+00:00, sha b70ce60246e3)
  - site_page: https://www.zipline.io/products/employee-compliance (fetched 2026-08-29T07:57:52.358692+00:00, sha 2863b87450f6)
  - site_page: https://www.zipline.io/products/contractor-compliance (fetched 2026-08-29T07:57:52.360786+00:00, sha a8326ca4d0b8)
- Data as of 2026-08-30T08:39:29.467469+00:00.