# PandaAI QuantFlow

Repository: https://github.com/PandaAI-Tech/panda_quantflow
Canonical: https://ross.abutalabs.com/products/pandaai-quantflow
Language: JavaScript
License: AGPL-3.0
License Family: copyleft
Last push: 2025-08-14T03:08:39+00:00

## Health v2 (maintenance only)
Score: 25/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 36, release rhythm 8, longevity 31
- inputs: {"age_days": 440, "days_push": 384, "days_rel": 440, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1037, forks 288 (observed 2026-08-28T04:03:19.471570+00:00)

## What it is
PandaFactor is a Python quantitative factor library for financial data analysis, technical indicator computation, and alpha factor construction, with built-in visualization charts. Factors can be written in Python (subclassing Factor) or via a formula DSL, backed by bundled market data with automatic nightly updates and optional LLM integration.

## Use cases
- compute quantitative alpha factors for stock data
- calculate technical indicators like momentum and volatility
- backtest custom trading factors in python
- build factors without coding using a formula language
- visualize factor performance charts
- auto-update market data from tushare or ricequant
- research factor ideas for a quant factor competition

## When to choose
- you research or build quantitative factors for Chinese A-share markets
- you want both Python and no-code formula ways to define factors
- you need bundled historical data with automatic nightly updates
- you want factor persistence and fast retrieval of computed factors

## When to avoid
- you need a full production trading execution system
- you require non-Chinese market data out of the box
- you need permissive licensing - it is AGPL-3.0
- you want a lightweight pure-python library without a MongoDB/local database dependency

## Facets
- artifact type: library
- maturity: active
- function: data-science, data-visualization, analytics, llm-inference, database
- domain: fintech, data-science, analytics
- platform: python, windows, self-hosted
- tags: quantitative-finance, factor-research, alpha-factors, technical-indicators, backtesting, a-share-market, formula-dsl, mongodb, trading, linux, macos

## Member repositories
- PandaAI-Tech/panda_quantflow (main) score 25
- PandaAI-Tech/panda_factor (sdk) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:19.471570+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 2026-08-30T08:14:32.130393+00:00, confidence not recorded.
  - readme: https://github.com/PandaAI-Tech/panda_quantflow (fetched 2026-08-28T04:03:19.471570+00:00, sha 4346b5dbdb11)
- Data as of 2026-08-30T08:39:29.467469+00:00.