# tradytics/surpriver

Find big moving stocks before they move using machine learning and anomaly detection

Repository: https://github.com/tradytics/surpriver
Canonical: https://ross.abutalabs.com/products/surpriver
Homepage: https://www.tradytics.com/
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: machine-learning, finance-application, trading, trading-algorithms, algotrading, anomaly-detection, ai, investment, stock-analysis, stock
Last push: 2021-08-13T08:02:31+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2194, "days_push": 1846, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1874, forks 338 (observed 2026-08-28T04:05:47.416118+00:00)

## What it is
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
- artifact type: application
- maturity: maintenance
- function: machine-learning, analytics, data-science
- domain: fintech, machine-learning, analytics
- platform: python, cross-platform
- tags: anomaly-detection, stock-screening, algorithmic-trading, technical-analysis, yahoo-finance, docker

## Member repositories
- tradytics/surpriver (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:47.416118+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 2026-08-30T03:14:48.893555+00:00, confidence not recorded.
  - readme: https://github.com/tradytics/surpriver (fetched 2026-08-28T04:05:47.416118+00:00, sha 8c878b99c13d)
  - homepage: https://www.tradytics.com/ (fetched 2026-08-29T10:53:53.255017+00:00, sha 098787206b61)
  - site_page: https://tradytics.com/support (fetched 2026-08-29T10:53:53.264354+00:00, sha a0deed7c6c12)
- Data as of 2026-08-30T08:39:29.467469+00:00.