{"id":13528675,"url":"https://github.com/DhiriaDev/TIMEX","last_synced_at":"2025-04-01T14:32:48.847Z","repository":{"id":49796704,"uuid":"307386342","full_name":"DhiriaDev/TIMEX","owner":"DhiriaDev","description":"Library for time-series-forecasting-as-a-service.","archived":false,"fork":false,"pushed_at":"2023-06-24T20:21:06.000Z","size":34552,"stargazers_count":15,"open_issues_count":0,"forks_count":3,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-03-24T12:15:56.071Z","etag":null,"topics":["forecasting","forecasting-a-a-service","machine-learning","time-series"],"latest_commit_sha":null,"homepage":"https://alexmv12.github.io/TIMEX/timexseries/index.html","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"agpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DhiriaDev.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2020-10-26T13:44:50.000Z","updated_at":"2024-11-30T12:52:36.000Z","dependencies_parsed_at":"2023-07-28T21:30:08.758Z","dependency_job_id":null,"html_url":"https://github.com/DhiriaDev/TIMEX","commit_stats":null,"previous_names":["alexmv12/timex"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DhiriaDev%2FTIMEX","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DhiriaDev%2FTIMEX/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DhiriaDev%2FTIMEX/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DhiriaDev%2FTIMEX/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DhiriaDev","download_url":"https://codeload.github.com/DhiriaDev/TIMEX/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246655215,"owners_count":20812600,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["forecasting","forecasting-a-a-service","machine-learning","time-series"],"created_at":"2024-08-01T07:00:22.623Z","updated_at":"2025-04-01T14:32:45.112Z","avatar_url":"https://github.com/DhiriaDev.png","language":"Jupyter Notebook","readme":"# TIMEX\n[![Tests with PyTest](https://github.com/AlexMV12/TIMEX/actions/workflows/run_tests.yml/badge.svg)](https://github.com/AlexMV12/TIMEX/actions/workflows/run_tests.yml)\n![Coverage](badges/coverage.svg)\n![PyPI](https://img.shields.io/pypi/v/timexseries)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/timexseries)\n\nTIMEX (referred in code as `timexseries`) is a framework for time-series-forecasting-as-a-service.\n\nIts main goal is to provide a simple and generic tool to build websites and, more in general,\nplatforms, able to provide the forecasting of time-series in the \"as-a-service\" manner.\n\nThis means that users should interact with the service as less as possible.\n\nAn example of the capabilities of TIMEX can be found at [covid-timex.it](https://covid-timex.it)  \nThat website is built using the [Dash](https://dash.plotly.com/), on which the visualization\npart of TIMEX is built. A deep explanation is available in the \n[dedicated repository](https://github.com/AlexMV12/covid-timex.it).\n\n## Installation\nThe main two dependencies of TIMEX are [Facebook Prophet](https://github.com/facebook/prophet)\nand [PyTorch](https://pytorch.org/). \nIf you prefer, you can install them beforehand, maybe because you want to choose the CUDA/CPU\nversion of Torch.\n\nHowever, installation is as simple as running:\n\n`pip install timexseries`\n\n## Get started\nPlease, refer to the Examples folder. You will find some Jupyter Notebook which illustrate\nthe main characteristics of TIMEX. A Notebook explaining the covid-timex.it website is present,\nalong with the source code of the site, [here](https://github.com/AlexMV12/covid-timex.it).\n\n## Documentation\nThe full documentation is available at [here](https://alexmv12.github.io/TIMEX/timexseries/index.html).\n\n## Contacts\nIf you have questions, suggestions or problems, feel free to open an Issue.\nYou can contact us at:\n\n- alessandro.falcetta@polimi.it\n- manuel.roveri@polimi.it\n\n","funding_links":[],"categories":["Libraries"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDhiriaDev%2FTIMEX","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FDhiriaDev%2FTIMEX","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDhiriaDev%2FTIMEX/lists"}