randomstatsmodels 0.1.0

Tools for benchmarking, metrics, and models.

randomstatsmodels

A tiny, modern Python package skeleton for experimenting with forecasting and statistics utilities.

Quick start

# from the project root
python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -e ".[dev]"  # install in editable mode with dev extras
randomstatsmodels --version

Usage

from randomstatsmodels.metrics import mae, rmse

y_true = [1, 2, 3]
y_pred = [1.1, 1.9, 3.2]
print(mae(y_true, y_pred))

Testing

pytest -q

Using your models

Put your custom models in randomstatsmodels/user_models.py (we copied your uploaded file there).

Python API

from randomstatsmodels.api import predict
# Model ref can be 'randomstatsmodels.user_models:MyModel' or an object/callable
yhat = predict("randomstatsmodels.user_models:MyModel", X_dataframe)

CLI

randomstatsmodels predict \        --model randomstatsmodels.user_models:MyModel \        --input data.csv \        --output preds.csv

The adapter accepts:

• Objects with .predict(X, **kwargs)
• Callables like def f(X): ...
• Classes that can be instantiated without args and have .predict(X)