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Functime

Functime is an open-source Python library for global forecasting and time-series feature extraction on large panel datasets. It uses Polars lazy transforms and includes preprocessing, cross-validation splitters and forecast metrics.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Functime — OpenViST project profile in AI Data & Analytics.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Functime when a Python workflow needs forecasting or feature extraction across panel time-series data, especially when parallel Polars transforms, backtesting or forecast metrics are useful.

Who it is for

  • Python practitioners forecasting multiple related time series.
  • Data teams engineering time-series features across panel datasets.
  • Practitioners who need backtesting and forecast scoring within a Polars-based workflow.

Documented uses

  • Build forecasts for multiple series in a panel dataset.
  • Extract time-series features from individual series or grouped panels.
  • Preprocess series and evaluate forecasts with metrics and time-based splitters.
  • Add exogenous regressors, transformations or optional forecasting integrations to a workflow.
Before you choose

Requirements & limits

Functime is an open-source Python library distributed under the Apache-2.0 license. The README documents installation with uv or pip.

  • The workflow is a Python library rather than a hosted forecasting application.
  • Polars is central to its lazy, parallel data-processing approach.
  • The README documents more than 100 time-series feature extractors and supports grouped extraction.
  • The LLM forecast analyst and LightGBM, CatBoost and XGBoost forecasters are optional extras.
  • Forecast examples specify the frequency, lag count and prediction horizon; exogenous regressors are passed as X.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install Functime

Add the Functime package to a Python project using one of the documented package managers.

Before you start

  • A Python project
  • Either uv or pip

Steps

  1. Run the command below to add Functime with uv.

    Documented command
    uv add functime

  2. Alternatively, run the command below to install it with pip.

    Documented command
    pip install functime

Expected outcome

The Functime package is installed in the project environment.

Guide limitations

  • This covers package installation only, not running a forecasting or feature-extraction workflow.
  • Optional integrations such as the LLM analyst and LightGBM forecaster require extras.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
13 October 2026
Original website title
functime-org/functime · Official homepage title · retained in its source language
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