Time Series Forecasting Python Packages

gluonts

Probabilistic time series modeling in Python

chronos-forecasting

Chronos: Pretrained Models for Time Series Forecasting

hierarchicalforecast

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

fev

Forecast evaluation library

nixtla

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

skforecast

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

tabpfn-time-series

Zero-shot Time Series Forecasting with TabPFN (work accepted at NeurIPS 2024 TRL and TSALM workshops)

eland

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

pytorchtime

Datasets, Transforms and Models specific to Time Series, powered by PyTorch

momentfm

MOMENT: A Family of Open Time-series Foundation Models, ICML'24

itransformer

Unofficial implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group

nixtlats

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

timecopilot-chronos-forecasting

Chronos: Pretrained Models for Time Series Forecasting

tsicl

TS-ICL: a Time-Indexed Foundation Model for Time Series Forecasting & Imputation via In-Context Learning

apdtflow

APDTFlow is a modern and extensible forecasting framework for time series data that leverages advanced techniques including neural ordinary differential equations (Neural ODEs), transformer-based components, and probabilistic modeling. Its modular design allows researchers and practitioners to experiment with multiple forecasting models and easily

fabba

A Python library for the fast symbolic approximation of time series

tsfmx

Multimodal extension for time series foundation models

pipelinets

⚡ Simplest and most professional TimeSeries forecasting + AutoML. Preprocess → Predict.

tsts

📈 toolset for time series forecasting

timecast-nightly

Performant, composable online learning

py-ssa-lib

Py-SSA-Lib: Python implementation of the multichannel singular spectrum analysis (MSSA) and singular spectrum analysis (SSA)

expsmoothing

A simple introduction to statistical learning for time-series forecasting using the Holt Simple Exponential Smoothing method

conformal-tights

👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster

spinests

spinesTS, a powerful timeseries toolsets.