# RJT1990/pyflux

Open source time series library for Python

Repository: https://github.com/RJT1990/pyflux
Canonical: https://ross.abutalabs.com/products/pyflux
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: statistics, time-series
Last push: 2023-10-24T16:13:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3851, "days_push": 1044, "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 2134, forks 244 (observed 2026-08-28T04:06:17.492057+00:00)

## What it is
PyFlux is an open source Python library for time series analysis and forecasting, offering a broad range of models such as ARIMA, GARCH, GAS, and state space models. It supports both frequentist and Bayesian inference options, enabling a probabilistic approach to time series modelling.

## Use cases
- forecast future values of a time series with ARIMA models
- model volatility in financial returns using GARCH or EGARCH
- fit Bayesian time series models with variational inference
- analyze multivariate time series with VAR models
- fit non-Gaussian state space models to count data
- run probabilistic forecasting with uncertainty estimates

## When to avoid
- you need actively maintained software with recent bug fixes and dependency updates
- you require production-grade stability, as the library is alpha software with limited test coverage
- you need deep learning based forecasting such as neural networks or transformers
- you need a library with strong community support and ongoing development

## Facets
- artifact type: library
- maturity: maintenance
- function: data-science, machine-learning
- domain: time-series, data-science
- platform: python
- tags: time-series-analysis, bayesian-inference, arima, garch, state-space-models, forecasting, statistics

## Member repositories
- RJT1990/pyflux (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:17.492057+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 2026-08-30T02:51:56.212540+00:00, confidence not recorded.
  - readme: https://github.com/RJT1990/pyflux (fetched 2026-08-28T04:06:17.492057+00:00, sha f16928999d9d)
  - registry_pypi: https://pypi.org/pypi/pyflux/json (fetched 2026-08-29T10:31:57.174576+00:00, sha 3a350d92747a)
- Data as of 2026-08-30T08:39:29.467469+00:00.