hyper-shell


Namehyper-shell JSON
Version 2.5.1 PyPI version JSON
download
home_pagehttps://hyper-shell.readthedocs.io
SummaryA cross-platform, high-throughput computing utility for processing shell commands over a distributed, asynchronous queue.
upload_time2024-05-26 17:34:25
maintainerNone
docs_urlNone
authorGeoffrey Lentner
requires_python<4.0,>=3.10
licenseApache-2.0
keywords distributed-computing command-line-tool shell-scripting high-performance-computing high-throughput-computing
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            HyperShell v2: Distributed Task Execution for HPC
=================================================

.. image:: https://img.shields.io/badge/license-Apache-blue.svg?style=flat
    :target: https://www.apache.org/licenses/LICENSE-2.0
    :alt: License

.. image:: https://img.shields.io/pypi/v/hyper-shell.svg?style=flat&color=blue
    :target: https://pypi.org/project/hyper-shell
    :alt: PyPI Version

.. image:: https://img.shields.io/pypi/pyversions/hyper-shell.svg?logo=python&logoColor=white&style=flat
    :target: https://pypi.org/project/hyper-shell
    :alt: Python Versions

.. image:: https://readthedocs.org/projects/hyper-shell/badge/?version=latest&style=flat
    :target: https://hyper-shell.readthedocs.io
    :alt: Documentation

.. image:: https://static.pepy.tech/badge/hyper-shell
    :target: https://pepy.tech/project/hyper-shell
    :alt: Downloads

|

    ⚠️⚠️⚠️**Warning** ⚠️⚠️⚠️

    **The ``hyper-shell`` PyPI package is deprecated use ``hypershell`` instead.**

    For backwards compatibility the ``hyper-shell`` PyPI package will remain
    inplace; however, new releases will not be published there.

|

*HyperShell* is an elegant, cross-platform, high-throughput computing utility for
processing shell commands over a distributed, asynchronous queue. It is a highly
scalable workflow automation tool for *many-task* scenarios.

Built on Python and tested on Linux, macOS, and Windows.

Several tools offer similar functionality but not all together in a single tool with
the user ergonomics we provide. Novel design elements include but are not limited to

* **Cross-platform:** run on any platform where Python runs. In fact, the server and
  client can run on different platforms in the same cluster.
* **Client-server:** workloads do not need to be monolithic. Run the server as a
  stand-alone service with SQLite or Postgres as a persistent database and dynamically
  scale clients as needed.
* **Staggered launch:** At the largest scales (1000s of nodes, 100k+ of workers),
  the launch process can be challenging. Come up gradually to balance the workload.
* **Database in-the-loop:** run in-memory for quick, ad-hoc workloads. Otherwise,
  include a database for persistence, recovery when restarting, and search.


Documentation
-------------

Documentation is available at `hyper-shell.readthedocs.io <https://hyper-shell.readthedocs.io>`_.
For basic usage information on the command line use: ``hyper-shell --help``. For a more 
comprehensive usage guide on the command line you can view the manual page with 
``man hyper-shell``.


Contributions
-------------

Contributions are welcome. If you find bugs or have questions, open an *Issue* here.
We've added a Code of Conduct recently, adapted from the
`Contributor Covenant <https://www.contributor-covenant.org/>`_, version 2.0.


Citation
--------

If *HyperShell* has helped in your research please consider citing us.

.. code-block:: bibtex

    @inproceedings{lentner_2022,
        author = {Lentner, Geoffrey and Gorenstein, Lev},
        title = {HyperShell v2: Distributed Task Execution for HPC},
        year = {2022},
        isbn = {9781450391610},
        publisher = {Association for Computing Machinery},
        url = {https://doi.org/10.1145/3491418.3535138},
        doi = {10.1145/3491418.3535138},
        booktitle = {Practice and Experience in Advanced Research Computing},
        articleno = {80},
        numpages = {3},
        series = {PEARC '22}
    }


            

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    "description": "HyperShell v2: Distributed Task Execution for HPC\n=================================================\n\n.. image:: https://img.shields.io/badge/license-Apache-blue.svg?style=flat\n    :target: https://www.apache.org/licenses/LICENSE-2.0\n    :alt: License\n\n.. image:: https://img.shields.io/pypi/v/hyper-shell.svg?style=flat&color=blue\n    :target: https://pypi.org/project/hyper-shell\n    :alt: PyPI Version\n\n.. image:: https://img.shields.io/pypi/pyversions/hyper-shell.svg?logo=python&logoColor=white&style=flat\n    :target: https://pypi.org/project/hyper-shell\n    :alt: Python Versions\n\n.. image:: https://readthedocs.org/projects/hyper-shell/badge/?version=latest&style=flat\n    :target: https://hyper-shell.readthedocs.io\n    :alt: Documentation\n\n.. image:: https://static.pepy.tech/badge/hyper-shell\n    :target: https://pepy.tech/project/hyper-shell\n    :alt: Downloads\n\n|\n\n    \u26a0\ufe0f\u26a0\ufe0f\u26a0\ufe0f**Warning** \u26a0\ufe0f\u26a0\ufe0f\u26a0\ufe0f\n\n    **The ``hyper-shell`` PyPI package is deprecated use ``hypershell`` instead.**\n\n    For backwards compatibility the ``hyper-shell`` PyPI package will remain\n    inplace; however, new releases will not be published there.\n\n|\n\n*HyperShell* is an elegant, cross-platform, high-throughput computing utility for\nprocessing shell commands over a distributed, asynchronous queue. It is a highly\nscalable workflow automation tool for *many-task* scenarios.\n\nBuilt on Python and tested on Linux, macOS, and Windows.\n\nSeveral tools offer similar functionality but not all together in a single tool with\nthe user ergonomics we provide. Novel design elements include but are not limited to\n\n* **Cross-platform:** run on any platform where Python runs. In fact, the server and\n  client can run on different platforms in the same cluster.\n* **Client-server:** workloads do not need to be monolithic. Run the server as a\n  stand-alone service with SQLite or Postgres as a persistent database and dynamically\n  scale clients as needed.\n* **Staggered launch:** At the largest scales (1000s of nodes, 100k+ of workers),\n  the launch process can be challenging. Come up gradually to balance the workload.\n* **Database in-the-loop:** run in-memory for quick, ad-hoc workloads. Otherwise,\n  include a database for persistence, recovery when restarting, and search.\n\n\nDocumentation\n-------------\n\nDocumentation is available at `hyper-shell.readthedocs.io <https://hyper-shell.readthedocs.io>`_.\nFor basic usage information on the command line use: ``hyper-shell --help``. For a more \ncomprehensive usage guide on the command line you can view the manual page with \n``man hyper-shell``.\n\n\nContributions\n-------------\n\nContributions are welcome. If you find bugs or have questions, open an *Issue* here.\nWe've added a Code of Conduct recently, adapted from the\n`Contributor Covenant <https://www.contributor-covenant.org/>`_, version 2.0.\n\n\nCitation\n--------\n\nIf *HyperShell* has helped in your research please consider citing us.\n\n.. code-block:: bibtex\n\n    @inproceedings{lentner_2022,\n        author = {Lentner, Geoffrey and Gorenstein, Lev},\n        title = {HyperShell v2: Distributed Task Execution for HPC},\n        year = {2022},\n        isbn = {9781450391610},\n        publisher = {Association for Computing Machinery},\n        url = {https://doi.org/10.1145/3491418.3535138},\n        doi = {10.1145/3491418.3535138},\n        booktitle = {Practice and Experience in Advanced Research Computing},\n        articleno = {80},\n        numpages = {3},\n        series = {PEARC '22}\n    }\n\n",
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