PyCaret 4.0 — the modern, minimalistic ML control pane on top of scikit-learn.
Project description
PyCaret 4.0 — engine
The PyCaret 4.0 engine. Config-driven, stateless, notebook-friendly, built on scikit-learn 1.7+ / NumPy 2 / pandas 2 / Python 3.11+.
Paired with services/api (the FastAPI backend) and
apps/web (the React UI) to form PyCaret Control Plane —
a self-hosted ML platform. But the engine works standalone in a notebook too:
from pycaret.datasets import get_data
from pycaret.tasks import ClassificationExperiment
df = get_data("juice")
exp = ClassificationExperiment(target="Purchase", session_id=42).fit(df)
best = exp.compare_models().best
exp.save_model(best, "baseline")
Status
4.0.0a1 on PyPI. Published wheel name: pycaret. See the repo root
docs/revamp/STATUS.md for the programme-wide
status and docs/revamp/ROADMAP.md for what's
next.
Layout
packages/engine/
├── pyproject.toml # builds the `pycaret` wheel
├── pycaret/ # the package
│ ├── api/ # list_models, describe_model, describe_setup_params
│ ├── core/ # Experiment base class + results + errors
│ ├── tasks/ # 5 task subclasses (classification/regression/...)
│ ├── logging/ # BaseLogger + events + MemoryLogger
│ ├── containers/ # model-registry containers (legacy, being drained)
│ └── internal/ # god-class (being drained verb-by-verb — Phase 5)
├── tests/ # pytest suite (32 tests)
└── README.md # this file
Dev
From the repo root:
uv sync --all-packages --all-extras # all workspace members + extras
uv run pytest packages/engine/tests/ -q # 32 engine tests
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