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facebook/prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. observed · 2026-10-14

github.com/facebook/prophet · homepage · Python · MIT (permissive) observed · 2026-10-14

Health v2 · maintenance only

99/100

  • Activity 99
  • Release rhythm 98
  • Longevity 100
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 13
  • age_days: 3626
  • days_rel: 15
  • days_push: 7
  • n_releases_24m: 10

Full methodology

Adoption not part of the score

20437 stars · 4637 forks observed · 2026-10-14

What it is AI-extracted, prompt v1, taxonomy v1, 2026-10-19, confidence 0.98

Prophet is an open‑source library for automatic forecasting of time‑series data with multiple seasonalities. It provides a simple API in Python and R and fits an additive model using Stan under the hood.

Use cases

  • generate weekly sales forecasts for retail stores
  • predict daily website traffic with holiday adjustments
  • model monthly demand for inventory planning
  • forecast energy consumption with yearly and weekly patterns
  • create quick baseline forecasts for financial time series

When to choose

  • you need fast, reasonably accurate forecasts without extensive model tuning
  • your data exhibits strong seasonal patterns and you have several seasons of history
  • you prefer a high‑level API in Python or R and want automatic handling of missing data and outliers

When to avoid

  • you require custom deep‑learning models or advanced probabilistic forecasting beyond additive components
  • real‑time low‑latency predictions are needed, as Prophet is designed for batch forecasting
  • you need extensive support for multivariate time series or complex exogenous regressors not covered by Prophet

Facets

library · maturity maintenance

machine-learning artificial-intelligence machine-learning data-science python time-series additive-model seasonality holiday-effects robust-to-outliers forecasting r

3 sources

Member repositories

RepositoryRoleHealth v2
facebook/prophetmain99

For agents

markdown · JSON · MCP: product_card(name="facebook/prophet")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem