{"adoption": {"forks": 874, "observed_at": "2026-08-28T04:09:33.889814+00:00", "stars": 5973}, "canonical_url": "https://ross.abutalabs.com/products/causalml", "card": {"archived": false, "artifact_type": "library", "description": "Uplift modeling and causal inference with machine learning algorithms", "domain": ["machine-learning", "data-science", "analytics"], "enriched": true, "function": ["machine-learning", "data-science"], "health_score": 98, "homepage": null, "language": "Python", "license": "NOASSERTION", "license_family": "other", "maturity": "stable", "member_repos": ["uber/causalml"], "name": "uber/causalml", "platform": ["python"], "pushed_at": "2026-08-20T15:25:36+00:00", "repo": "uber/causalml", "stars": 5973, "tags": ["causal-inference", "uplift-modeling", "treatment-effect", "cate", "a-b-testing", "marketing-analytics"], "topics": ["incubation", "machine-learning", "causal-inference", "uplift-modeling"], "urls": [], "use_cases": ["estimate heterogeneous treatment effects from A/B test data", "optimize ad campaign targeting by uplift score", "personalize customer engagement and treatment recommendations", "estimate conditional average treatment effect from observational data", "compare uplift modeling estimators like meta-learners and causal forests", "measure incremental impact of marketing interventions on sales"], "what_it_is": "Causal ML is a Python package providing uplift modeling and causal inference methods built on machine learning algorithms. It estimates the Conditional Average Treatment Effect (CATE) from experimental or observational data through a standard estimator interface.", "when_to_avoid": ["you need plain supervised prediction without causal interpretation", "you require strict API stability, since some experimental APIs may change", "you need deep-learning-based causal estimation beyond the provided estimator families"], "when_to_choose": ["you need to estimate individual-level causal effects of a treatment or intervention", "you want to target customers by predicted uplift rather than predicted outcome", "you have A/B experiment or observational data with features, treatment, and outcome", "you want a maintained Python library with many CATE estimators behind one interface"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/causalml", "repo": "uber/causalml", "role": "main", "score": 88}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:09:33.889814+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T17:50:08.558522+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "7cf4d6987ef204baeddbde4da2f228b4fbd9a3e3989161d3891cf204ae638956", "fetched_at": "2026-08-28T04:09:33.889814+00:00", "kind": "readme", "missing": false, "url": "https://github.com/uber/causalml"}, {"content_hash": "bfda9ca4ad1212029b8add20dd21a0d2002f5efc838c0d6b9f8e922ea154b03f", "fetched_at": "2026-08-29T08:46:00.817383+00:00", "kind": "registry_pypi", "missing": false, "url": "https://pypi.org/pypi/causalml/json"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 98, "longevity": 100, "rhythm": 67}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2613, "days_push": 13, "days_rel": 60, "gap_med": 142, "n_releases_24m": 6}, "score": 88, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}