Skip to main content

Autosubmit is a Python-based workflow manager to create, manage and monitor complex tasks involving different substeps, such as scientific computational experiments. These workflows may involve multiple computing systems for their completion, from HPCs to post-processing clusters or workstations. Autosubmit can orchestrate all the tasks integrating the workflow by managing their dependencies, interfacing with all the platforms involved, and handling eventual errors.

Project description

Autosubmit is a lightweight workflow manager designed to meet climate research necessities. Unlike other workflow solutions in the domain, it integrates the capabilities of an experiment manager, workflow orchestrator and monitor in a self-contained application. The experiment manager allows for defining and configuring experiments, supported by a hierarchical database that ensures reproducibility and traceability. The orchestrator is designed to run complex workflows in research and operational mode by managing their dependencies and interfacing with local and remote hosts. These multi-scale workflows can involve from a few to thousands of steps and from one to multiple platforms.

Autosubmit facilitates easy and fast integration and relocation on new platforms. On the one hand, users can rapidly execute general scripts and progressively parametrize them by reading Autosubmit variables. On the other hand, it is a self-contained desktop application capable of submitting jobs to remote platforms without any external deployment.

Due to its robustness, it can handle different eventualities, such as networking or I/O errors. Finally, the monitoring capabilities extend beyond the desktop application through a REST API that allows communication with workflow monitoring tools such as the Autosubmit web GUI.

Autosubmit is a Python package provided in PyPI. Conda recipes can also be found on the website. A containerized version for testing purposes is also available but not public yet.

It has contributed to various European research projects and runs different operational systems. During the following years, it will support some of the Earth Digital Twins as the Digital Twin Ocean.

Concretely, it is currently used at Barcelona Supercomputing Centre (BSC) to run models (EC-Earth, MONARCH, NEMO, CALIOPE, HERMES…), operational toolchains (S2S4E), data-download workflows (ECMWF MARS), and many other. Autosubmit has run these workflows in different supercomputers in BSC, ECMWF, IC3, CESGA, EPCC, PDC, and OLCF.

Project details


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

autosubmit-4.0.73.tar.gz (6.1 MB view details)

Uploaded Source

Built Distribution

autosubmit-4.0.73-py3-none-any.whl (376.4 kB view details)

Uploaded Python 3

File details

Details for the file autosubmit-4.0.73.tar.gz.

File metadata

  • Download URL: autosubmit-4.0.73.tar.gz
  • Upload date:
  • Size: 6.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.22.0 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.30.0 importlib-metadata/4.11.1 keyring/18.0.1 rfc3986/2.0.0 colorama/0.4.3 CPython/3.8.10

File hashes

Hashes for autosubmit-4.0.73.tar.gz
Algorithm Hash digest
SHA256 edf0466435d6cc8051e558747c7ad8e908f8c30163587e9dae1c2941d519cb5e
MD5 172c21957afc809b542bbd5ad330b9f7
BLAKE2b-256 bca8f59396a42449698d7441412c8c83382b2a9324164cb21d10e9691e9c2c0d

See more details on using hashes here.

File details

Details for the file autosubmit-4.0.73-py3-none-any.whl.

File metadata

  • Download URL: autosubmit-4.0.73-py3-none-any.whl
  • Upload date:
  • Size: 376.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.22.0 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.30.0 importlib-metadata/4.11.1 keyring/18.0.1 rfc3986/2.0.0 colorama/0.4.3 CPython/3.8.10

File hashes

Hashes for autosubmit-4.0.73-py3-none-any.whl
Algorithm Hash digest
SHA256 f7df6fd4a7caf9fc224d88be5b0c7cab521417b404d563b37572a01a7629ae5a
MD5 f9f697ff6ba9efbedce8429a92a9853b
BLAKE2b-256 43759b93abeb386ac4d8e62ed5d16ff20513f58b2adbf5ca4b2bf06d152eab07

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page