tradytics/surpriver
Find big moving stocks before they move using machine learning and anomaly detection observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- 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: 2194
- days_rel: n/a
- days_push: 1846
- n_releases_24m: 0
Adoption not part of the score
1874 stars · 338 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Surpriver is a Python application that uses machine learning and anomaly detection to find stocks with unusual price and volume patterns that may precede large moves. It analyzes hourly candles with technical indicators and ranks the most anomalous stocks for the day.
Use cases
- find big moving stocks before they move
- screen stocks for unusual volume and price patterns
- anomaly detection on stock price action
- get daily list of most anomalous stocks
- build a stock screener with machine learning
- analyze technical indicators across the whole market
When to choose
- you want a free, self-hosted ML-based stock screener
- you want to run anomaly detection on hourly price/volume data from Yahoo Finance
- you are comfortable with Python or Docker and want customizable screening parameters
When to avoid
- you need real-time intraday signals or live data feeds
- you want a polished GUI or managed service rather than a CLI script
- you need actively maintained software - the last release was in 2021
- you expect guaranteed trading profits - anomaly scores are not trade signals
Facets
application · maturity maintenance
machine-learning analytics data-science fintech machine-learning analytics python cross-platform anomaly-detection stock-screening algorithmic-trading technical-analysis yahoo-finance docker
3 sources
- readme: https://github.com/tradytics/surpriver · fetched 2026-08-28 · 8c878b99c13d
- homepage: https://www.tradytics.com/ · fetched 2026-08-29 · 098787206b61
- site_page: https://tradytics.com/support · fetched 2026-08-29 · a0deed7c6c12
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tradytics/surpriver | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="tradytics/surpriver")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem