CamDavidsonPilon/lifetimes
Lifetime value in Python observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 8
- Longevity 100
Flags: archived
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: 4265
- days_rel: n/a
- days_push: 796
- n_releases_24m: 0
Adoption not part of the score
1476 stars · 373 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python library for measuring customer lifetime value (CLV) and modeling repeat-purchase behavior using probabilistic models like BG/NBD and Pareto/NBD. It is now archived, with PyMC-Marketing named as its successor.
Use cases
- predict customer lifetime value in python
- estimate how often customers will make repeat purchases
- predict which app users have churned from usage history
- model customer purchase frequency and recency
- analyze repeat visitor behavior on a website
When to choose
- you need classic BG/NBD or Pareto/NBD CLV models in a lightweight pandas-friendly library
- you're maintaining legacy code that already depends on lifetimes
When to avoid
- you're starting a new project - use PyMC-Marketing instead
- you need bug fixes, new features, or issue support, since the repo is archived
Facets
library · maturity abandoned
data-science analytics data-science analytics e-commerce python customer-lifetime-value clv bgnbd pareto-nbd survival-analysis churn-prediction statistics
2 sources
- readme: https://github.com/CamDavidsonPilon/lifetimes · fetched 2026-08-28 · 53c9634d1116
- registry_pypi: https://pypi.org/pypi/lifetimes/json · fetched 2026-08-29 · 0a18da88f582
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| CamDavidsonPilon/lifetimes | main | 10 |
For agents
markdown · JSON · MCP: product_card(name="CamDavidsonPilon/lifetimes")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem