Open short term energy forecaster
Project description
OpenSTEF
OpenSTEF is a Python package designed for generating short-term forecasts in the energy sector. The repository includes all the essential components required for machine learning pipelines that facilitate the forecasting process. To utilize the package, users are required to furnish their own data storage and retrieval interface.
Table of contents
- OpenSTEF
- Table of contents
- External information sources
- Installation
- Usage
- License
- Contributing
- Contact
External information sources
- Documentation website;
- Python package;
- Linux Foundation project page;
- Documentation on dashboard;
- Video about OpenSTEF;
- Teams channel
Installation
Install the openstef package
pip install openstef
Remark regarding installation within a conda environment on Windows:
A version of the pywin32 package will be installed as a secondary dependency along with the installation of the openstef package. Since conda relies on an old version of pywin32, the new installation can break conda's functionality. The following command can solve this issue:
pip install pywin32==300
For more information on this issue see the readme of pywin32 or this Github issue.
Usage
Example notebooks
To help you get started, a set of fundamental example notebooks has been created. You can access these offline examples here.
Reference Implementation
A complete implementation including databases, user interface, example data, etc. is available at: https://github.com/OpenSTEF/openstef-reference
To run a task use:
python -m openstef task <task_name>
Database connector for openstef
This repository provides an interface to OpenSTEF (reference) databases. The repository can be found here.
License
This project is licensed under the Mozilla Public License, version 2.0 - see LICENSE for details.
Licenses third-party libraries
This project includes third-party libraries, which are licensed under their own respective Open-Source licenses. SPDX-License-Identifier headers are used to show which license is applicable. The concerning license files can be found in the LICENSES directory.
Contributing
Please read CODE_OF_CONDUCT.md, CONTRIBUTING.md and PROJECT_GOVERNANCE.md for details on the process for submitting pull requests to us.
Contact
Please read SUPPORT.md for how to connect and get into contact with the OpenSTEF project
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file openstef-3.4.24.tar.gz.
File metadata
- Download URL: openstef-3.4.24.tar.gz
- Upload date:
- Size: 62.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9e7a51bc404d9362f7c8af600a3cb255b9de7958d86b5ff482748c87025ed9d3
|
|
| MD5 |
73965b2bbdf3034b39cd1fbacd813954
|
|
| BLAKE2b-256 |
a307f7dc5d7029ea6339d55e9e11b6ef98e4a0e7294a39e2fbbdc190c39ed747
|
File details
Details for the file openstef-3.4.24-py3-none-any.whl.
File metadata
- Download URL: openstef-3.4.24-py3-none-any.whl
- Upload date:
- Size: 62.2 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c206195bdcf138250472ae64b3d5777cc1917725f04f8061781827b74a3bf376
|
|
| MD5 |
71905d6003d27492235b2d20e8858b36
|
|
| BLAKE2b-256 |
c19885f43f8113ad38617f59a25e3fd759bdc6801ad7f19bd1a76543e07f3450
|
