earthkit-workflows-anemoi

[!IMPORTANT] This software is Sandbox and subject to ECMWF's guidelines on Software Maturity.

Earthkit-Workflows-Anemoi is a Python library for connecting anemoi-inference to earthkit-workflows. Allowing for the inference tasks to be run as part of a larger DAG. It provides an API to directly create a graph consisting of initial condition retrieval and model execution, or to run inference off other source nodes which themselves are the initial conditions.

Installation

The package has a split dependency structure to allow flexible installation:

For workflow creation (minimal)

To create workflows without running them locally:

pip install earthkit-workflows-anemoi

This installs only the core dependencies needed to define and serialize workflows.

For workflow execution (full runtime)

To both create and execute workflows locally:

pip install 'earthkit-workflows-anemoi[runtime]'

This includes anemoi-inference and anemoi-datasets required for local execution.

For development

git clone https://github.com/ecmwf/earthkit-workflows-anemoi.git
cd earthkit-workflows-anemoi
pip install -e '.[dev]'

Additionally you may want to install pre-commit hooks:

pip install pre-commit
pre-commit install

Quick Start

To create a graph relying on anemoi-inference to get the initial conditions the following can be used:

from earthkit.workflows.plugins import anemoi as anemoi_workflows

CKPT = {'huggingface': 'ecmwf/aifs-single-1.0'}

model_action = anemoi_workflows.fluent.from_input(CKPT, 'mars', '2022-01-01T00:00', lead_time = '7D', ensemble_members=51)
model_action

Note: For models with multiple datasets (supported since anemoi-inference 0.11.0), the resulting action includes a dataset dimension. Use .select({"dataset": "era5"}) to select a specific dataset if needed.

Given other nodes as the initial conditions:

from earthkit.workflows.plugins import anemoi as anemoi_workflows
from earthkit.workflows import fluent

SOURCE_NODES: fluent.Action
CKPT = {'huggingface': 'ecmwf/aifs-single-1.0'}

SOURCE_NODES.anemoi.infer(CKPT, lead_time = '7D', ensemble_members = 51)

Release files for earthkit-workflows-anemoi 0.7.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for earthkit-workflows-anemoi 0.7.3
File	Size	Uploaded
earthkit_workflows_anemoi-0.7.3.tar.gz	51.6 kB	Jun 19, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for earthkit-workflows-anemoi 0.7.3
File	Interpreter	ABI	Platform	Reset
earthkit_workflows_anemoi-0.7.3-py3-none-any.whl 24.2 kB Jun 19, 2026	Python 3	none	any	Details

Total release size: 75.8 kB

Release files / earthkit_workflows_anemoi-0.7.3.tar.gz

Download URL	earthkit_workflows_anemoi-0.7.3.tar.gz
Size	51.6 kB
Tags	Source
SHA-256 checksum How to use checksums	`ba57a0b776bbc2f05b72eb1cb7a54e473852189d324c5cda337d43dcd60f0a3b`
BLAKE2b-256 checksum How to use checksums	`07d1d2ca34b8fea078ae5b0e764aa89df2a3ff49f34d3520a34f56e7ae21cbb9`
Upload date	Jun 19, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.14.6`

Release files / earthkit_workflows_anemoi-0.7.3-py3-none-any.whl

Download URL	earthkit_workflows_anemoi-0.7.3-py3-none-any.whl
Size	24.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`1896f90760788d8106b7e084bc0934381aa25c6185c92f8b6b10df37bad98e29`
BLAKE2b-256 checksum How to use checksums	`aa8e4214e188f483ab483cf30023c8ded362f9bea9f7f9d7d35bfc408876f72f`
Upload date	Jun 19, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.14.6`