Installation#

numeraire requires Python 3.11 or newer. Its runtime dependencies are the scientific-Python core only — numpy, scipy, pandas, and scikit-learn.

From PyPI#

pip install numeraire

The base install is the spine — the point-in-time views, the walk-forward engine, the native evaluators, the statistical tests, and the result schema — plus the universal baselines. It carries no method-specific or plotting dependencies.

Extras#

Opt into the companion packages and optional integrations through extras:

Extra	Pulls in	For
`numeraire[all]`	`numeraire-graphics` + `numeraire-dataset`	the full companion ecosystem
`numeraire[graphics]`	`numeraire-graphics`	grammar-of-graphics figures over results and Output objects
`numeraire[data]`	`numeraire-dataset`	open, reproducible data loaders and point-in-time builders
`numeraire[skfolio]`	`skfolio`	the constrained-portfolio-optimizer adapter

pip install "numeraire[all]"

Each companion package also installs on its own (pip install numeraire-graphics) and depends back on a compatible numeraire; see The ecosystem.

With uv#

In a uv-managed project:

uv add numeraire            # or: uv add "numeraire[all]"

From source (development)#

git clone https://github.com/py-numeraire/numeraire
cd numeraire
uv sync --extra dev         # spine + the full development toolchain

The development environment adds ruff, basedpyright, import-linter, pytest, and the docs toolchain. The standard checks:

uv run ruff check . && uv run ruff format --check .
uv run basedpyright src/numeraire/core     # strict types on the spine
uv run lint-imports                        # the architecture boundary
uv run pytest                              # tests (public / synthetic data only)

Verify#

from importlib.metadata import version

import numeraire  # noqa: F401

print(version("numeraire"))