| Name | pyearthtools JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | None |
| Summary | PyEarthTools: Machine learning for Earth system science. |
| upload_time | 2025-09-04 00:47:38 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | None |
| keywords |
pyearthtools
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# PyEarthTools: Machine learning for Earth system science
[](https://doi.org/10.5281/zenodo.15760768)
- An approachable way for researchers to get started with ML research for Earth system science
- Provides a software framework for research and experimentation
- Also suitable for students and newcomers
- Still under early-stage development - things are likely to change a lot. If you notice an issue, please feel free to raise it on GitHub
|<br>A weather prediction from a model trained with PyEarthTools.|<br>A data processing flow composed for working with climate data.|
|:-:|:-:|
Source Code: [github.com/ACCESS-Community-Hub/PyEarthTools](https://github.com/ACCESS-Community-Hub/PyEarthTools)
Documentation: [pyearthtools.readthedocs.io](https://pyearthtools.readthedocs.io)
Tutorial Gallery: [available here](https://pyearthtools.readthedocs.io/en/latest/notebooks/Gallery.html)
New Users Guide: [available here](https://pyearthtools.readthedocs.io/en/latest/newuser.html)
## Installation
**Here is the quickest way to install the complete framework and get started:**
We strongly recommend using either a Conda or Python [virtual environment](https://pyearthtools.readthedocs.io/en/latest/installation.html#virtual-environments).
Run the following commands to install PyEarthTools in a Conda environment:
```shell
git clone git@github.com:ACCESS-Community-Hub/PyEarthTools.git
conda create -y -p ./venv python graphviz
conda activate ./venv
pip install -r requirements.txt
cd notebooks
jupyter lab
```
Alternatively, run the following commands to install PyEarthTools in a Python virtual environment:
```shell
git clone git@github.com:ACCESS-Community-Hub/PyEarthTools.git
python3 -m venv ./venv
source venv/bin/activate
pip install -r requirements.txt
cd notebooks
jupyter lab
```
> [!TIP]
> (Optional) Install [Graphviz](https://graphviz.org/download/) (not installable via pip) to display pipelines.
PyEarthTools comprises multiple sub-packages which may be installed and used separately. See the [installation guide](https://pyearthtools.readthedocs.io/en/latest/installation.html) for more details.
## Overview of PyEarthTools
PyEarthTools is a Python framework containing modules for:
- loading and fetching data;
- pre-processing, normalising and standardising data into a normal form suitable for machine learning;
- defining machine learning (ML) models;
- training ML models and managing experiments;
- performing inference with ML models;
- and evaluating ML models.
## Overview of the Packages within PyEarthTools
PyEarthTools comprises multiple sub-packages which can be used individually or together.
| Sub-Package | Purpose |
|--------------------------------|---------------------- |
| [Data](https://pyearthtools.readthedocs.io/en/latest/api/data/data_index.html) | Loading and indexing Earth system data into xarray |
| [Utils](https://pyearthtools.readthedocs.io/en/latest/api/utils/utils_index.html) | Code for common functionality across the sub-packages |
| [Pipeline](https://pyearthtools.readthedocs.io/en/latest/api/pipeline/pipeline_index.html) | Process and normalise Earth system data ready for machine learning |
| [Training](https://pyearthtools.readthedocs.io/en/latest/api/training/training_index.html) | Training processes for machine learning models |
| [Tutorial](https://pyearthtools.readthedocs.io/en/latest/api/tutorial/tutorial_index.html) | Contains helper code for data sets used in tutorials |
| [Bundled Models](https://pyearthtools.readthedocs.io/en/latest/api/bundled_models/bundled_index.html) | Maintained versions of specific, bundled models which can be easily trained and run |
| [Zoo](https://pyearthtools.readthedocs.io/en/latest/api/zoo/zoo_index.html) | Contains code for managing registered models (such as the bundled models) |
| Evaluation | (Coming soon) Contains code for producing standard evaluations (such as benchmarks and scorecards) |
## Acknowleging or Citing `PyEarthTools`
If you use PyEarthTools for your work, we would appreciate you citing our software as below:
Cook, H., Leeuwenburg, T., Rio, M., Miller, J., Mason, G., Ramanathan, N., Pill, J., Haddad, S., & de Burgh-Day, C. (2025). PyEarthTools: Machine learning for Earth system science (0.1.1). Zenodo. https://doi.org/10.5281/zenodo.15760769
BibTeX:
```
@software{cook_2025_15760769,
author = {Cook, Harrison and
Leeuwenburg, Tennessee and
Rio, Maxime and
Miller, Joel and
Mason, Gemma and
Ramanathan, Nikeeth and
Pill, John and
Haddad, Stephen and
de Burgh-Day, Catherine},
title = {{PyEarthTools: Machine learning for Earth system science}},
month = jun,
year = 2025,
publisher = {Zenodo},
version = {0.1.1},
doi = {10.5281/zenodo.15760769},
url = {https://doi.org/10.5281/zenodo.15760769}
}
```
Raw data
{
"_id": null,
"home_page": null,
"name": "pyearthtools",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.11",
"maintainer_email": "Tennessee Leeuwenburg <tennessee.leeuwenburg@bom.gov.au>",
"keywords": "pyearthtools",
"author": null,
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/f2/9b/1e059a4bc53f9839f6fd8ee4a75874c83a9b0529351db7ddbe86fc86e615/pyearthtools-0.2.0.tar.gz",
"platform": null,
"description": "# PyEarthTools: Machine learning for Earth system science\n\n[](https://doi.org/10.5281/zenodo.15760768)\n\n- An approachable way for researchers to get started with ML research for Earth system science\n- Provides a software framework for research and experimentation\n- Also suitable for students and newcomers\n- Still under early-stage development - things are likely to change a lot. If you notice an issue, please feel free to raise it on GitHub\n\n|<br>A weather prediction from a model trained with PyEarthTools.|<br>A data processing flow composed for working with climate data.|\n|:-:|:-:|\n\nSource Code: [github.com/ACCESS-Community-Hub/PyEarthTools](https://github.com/ACCESS-Community-Hub/PyEarthTools) \nDocumentation: [pyearthtools.readthedocs.io](https://pyearthtools.readthedocs.io) \nTutorial Gallery: [available here](https://pyearthtools.readthedocs.io/en/latest/notebooks/Gallery.html) \nNew Users Guide: [available here](https://pyearthtools.readthedocs.io/en/latest/newuser.html) \n\n## Installation\n\n**Here is the quickest way to install the complete framework and get started:**\n\nWe strongly recommend using either a Conda or Python [virtual environment](https://pyearthtools.readthedocs.io/en/latest/installation.html#virtual-environments).\n\nRun the following commands to install PyEarthTools in a Conda environment:\n```shell\ngit clone git@github.com:ACCESS-Community-Hub/PyEarthTools.git\nconda create -y -p ./venv python graphviz\nconda activate ./venv\npip install -r requirements.txt\ncd notebooks\njupyter lab\n```\n\nAlternatively, run the following commands to install PyEarthTools in a Python virtual environment:\n```shell\ngit clone git@github.com:ACCESS-Community-Hub/PyEarthTools.git\npython3 -m venv ./venv\nsource venv/bin/activate\npip install -r requirements.txt\ncd notebooks\njupyter lab\n```\n> [!TIP]\n> (Optional) Install [Graphviz](https://graphviz.org/download/) (not installable via pip) to display pipelines.\n\nPyEarthTools comprises multiple sub-packages which may be installed and used separately. See the [installation guide](https://pyearthtools.readthedocs.io/en/latest/installation.html) for more details.\n\n## Overview of PyEarthTools\n\nPyEarthTools is a Python framework containing modules for:\n - loading and fetching data;\n - pre-processing, normalising and standardising data into a normal form suitable for machine learning;\n - defining machine learning (ML) models;\n - training ML models and managing experiments;\n - performing inference with ML models;\n - and evaluating ML models.\n\n## Overview of the Packages within PyEarthTools\n\nPyEarthTools comprises multiple sub-packages which can be used individually or together.\n\n| Sub-Package | Purpose |\n|--------------------------------|---------------------- |\n| [Data](https://pyearthtools.readthedocs.io/en/latest/api/data/data_index.html) | Loading and indexing Earth system data into xarray |\n| [Utils](https://pyearthtools.readthedocs.io/en/latest/api/utils/utils_index.html) | Code for common functionality across the sub-packages |\n| [Pipeline](https://pyearthtools.readthedocs.io/en/latest/api/pipeline/pipeline_index.html) | Process and normalise Earth system data ready for machine learning |\n| [Training](https://pyearthtools.readthedocs.io/en/latest/api/training/training_index.html) | Training processes for machine learning models |\n| [Tutorial](https://pyearthtools.readthedocs.io/en/latest/api/tutorial/tutorial_index.html) | Contains helper code for data sets used in tutorials |\n| [Bundled Models](https://pyearthtools.readthedocs.io/en/latest/api/bundled_models/bundled_index.html) | Maintained versions of specific, bundled models which can be easily trained and run |\n| [Zoo](https://pyearthtools.readthedocs.io/en/latest/api/zoo/zoo_index.html) | Contains code for managing registered models (such as the bundled models) |\n| Evaluation | (Coming soon) Contains code for producing standard evaluations (such as benchmarks and scorecards) |\n\n## Acknowleging or Citing `PyEarthTools`\n\nIf you use PyEarthTools for your work, we would appreciate you citing our software as below:\n\nCook, H., Leeuwenburg, T., Rio, M., Miller, J., Mason, G., Ramanathan, N., Pill, J., Haddad, S., & de Burgh-Day, C. (2025). PyEarthTools: Machine learning for Earth system science (0.1.1). Zenodo. https://doi.org/10.5281/zenodo.15760769\n\nBibTeX:\n```\n@software{cook_2025_15760769,\n author = {Cook, Harrison and\n Leeuwenburg, Tennessee and\n Rio, Maxime and\n Miller, Joel and\n Mason, Gemma and\n Ramanathan, Nikeeth and\n Pill, John and\n Haddad, Stephen and\n de Burgh-Day, Catherine},\n title = {{PyEarthTools: Machine learning for Earth system science}},\n month = jun,\n year = 2025,\n publisher = {Zenodo},\n version = {0.1.1},\n doi = {10.5281/zenodo.15760769},\n url = {https://doi.org/10.5281/zenodo.15760769}\n}\n```\n",
"bugtrack_url": null,
"license": null,
"summary": "PyEarthTools: Machine learning for Earth system science. ",
"version": "0.2.0",
"project_urls": {
"documentation": "https://pyearthtools.readthedocs.io/",
"homepage": "https://pyearthtools.readthedocs.io/",
"repository": "https://github.com/ACCESS-Community-Hub/PyEarthTools"
},
"split_keywords": [
"pyearthtools"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "ad5e9005a0ab446f3adc070460fd535be8aa0dab56bf3a6a380465eb6b671f42",
"md5": "6ad4410d1c48f4a55cb1dabfbfc890f3",
"sha256": "dd5750f52aa469a43f8a2481216b4bbe85ff1337400c47424dc3c1a9c06a20ec"
},
"downloads": -1,
"filename": "pyearthtools-0.2.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "6ad4410d1c48f4a55cb1dabfbfc890f3",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.11",
"size": 8850,
"upload_time": "2025-09-04T00:47:37",
"upload_time_iso_8601": "2025-09-04T00:47:37.739172Z",
"url": "https://files.pythonhosted.org/packages/ad/5e/9005a0ab446f3adc070460fd535be8aa0dab56bf3a6a380465eb6b671f42/pyearthtools-0.2.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "f29b1e059a4bc53f9839f6fd8ee4a75874c83a9b0529351db7ddbe86fc86e615",
"md5": "e5f4a16fed754232001d0e923845bd66",
"sha256": "470c57e6f2632bffc0793c82fd2f9444364b8d00f4969cf266aa4d44a5853db0"
},
"downloads": -1,
"filename": "pyearthtools-0.2.0.tar.gz",
"has_sig": false,
"md5_digest": "e5f4a16fed754232001d0e923845bd66",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.11",
"size": 9892,
"upload_time": "2025-09-04T00:47:38",
"upload_time_iso_8601": "2025-09-04T00:47:38.885484Z",
"url": "https://files.pythonhosted.org/packages/f2/9b/1e059a4bc53f9839f6fd8ee4a75874c83a9b0529351db7ddbe86fc86e615/pyearthtools-0.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-09-04 00:47:38",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ACCESS-Community-Hub",
"github_project": "PyEarthTools",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "pyearthtools"
}
