{
    "info": {
        "author": "Metabolize",
        "author_email": "github@paulmelnikow.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: System :: Distributed Computing"
        ],
        "description": "# werkit\n\n[![version](https://img.shields.io/pypi/v/werkit.svg?style=flat-square)][pypi]\n[![python versions](https://img.shields.io/pypi/pyversions/werkit.svg?style=flat-square)][pypi]\n[![license](https://img.shields.io/pypi/l/werkit.svg?style=flat-square)][pypi]\n[![build](https://img.shields.io/circleci/project/github/metabolize/werkit/master.svg?style=flat-square)][build]\n[![code style](https://img.shields.io/badge/code%20style-black-black.svg?style=flat-square)][black]\n\nToolkit for encapsulating Python-based computation into deployable and\ndistributable tasks.\n\nProvides code that helps package things up:\n\n- Serializing results\n- Handling and serializing errors\n- Deploying task workers using [Redis][], [RQ][] and the [Fargate CLI][]\n\n[redis]: https://redis.io/\n[rq]: https://python-rq.org/\n[fargate cli]: https://somanymachines.com/fargate/\n\nThey're particularly useful for providing repsonse consistency across different\nrevisions of a service or different services.\n\n[pypi]: https://pypi.org/project/werkit/\n[coverage]: https://coveralls.io/github/metabolize/werkit\n[build]: https://circleci.com/gh/lace/werkit/tree/master\n[docs build]: https://werkit.readthedocs.io/en/latest/\n[black]: https://black.readthedocs.io/en/stable/\n\n## Installation\n\n```sh\npip install werkit\n```\n\n## Usage\n\n```py\nfrom werkit import Manager\n\ndef myfunc(param, verbose=False, handle_exceptions=True):\n    with Manager(handle_exceptions=handle_exceptions, verbose=verbose) as manager:\n        manager.result = do_some_computation()\n    return manager.serialized_result\n```\n\n## Parallel computation\n\nWerkit supports parallel computation using Redis and RQ.\n\nYou must install the dependencies separately:\n\n```sh\npip install redis rq\n```\n\n### Requesting work\n\n```py\nfrom mylib import myfunc\nfrom werkit.parallel import invoke_for_each\n\n\nitems = {'a': ..., 'b': ...}\njob_ids = invoke_for_each(myfunc, items, connection=Redis.from_url(...))\n```\n\n### Performing work\n\n```sh\npip install redis rq\nrq worker --burst werkit-default --url rediss://...\n```\n\nNote: `mylib.myfunc` must be importable.\n\n### Using CloudManager\n\nIn place of the low-level API you can make your calls using CloudManager:\n\n```py\n#!/usr/bin/env python\n\n\nimport click\nfrom werkit.parallel import Config, CloudManager, invoke_for_each\n\nmanager = CloudManager(\n    config=Config(\n        local_repository=\"my-project\",\n        ecr_repository=\"123456789012.dkr.ecr.us-east-1.amazonaws.com/my-project\",\n        ecs_task_name=\"my-project\",\n        task_args=[\n            \"--cpu\",\n            \"1024\",\n            \"--memory\",\n            \"2048\",\n            \"--task-role\",\n            \"arn:aws:iam::123456789012:role/...\",\n            \"--security-group-id\",\n            \"sg-...\",\n            \"--subnet-id\",\n            \"subnet-...\",\n        ],\n        default_task_count=5,\n    )\n)\n\n\n@click.group()\ndef cli():\n    pass\n\n\n@cli.command()\ndef login():\n    manager.login()\n\n\n@cli.command()\n@click.argument(\"tag\")\ndef build_and_push(tag):\n    manager.build_and_push()\n\n\n@cli.command()\ndef enqueue():\n    from myproject import myfunc\n\n    items = {\"key1\": \"value1\", \"key2\": \"value2\"}\n\n    invoke_for_each(\n        measure_body,\n        items,\n        clean=True,\n        connection=manager.redis_connection,\n    )\n\n\n@cli.command()\n@click.option(\n    \"--count\",\n    default=manager.config.default_task_count,\n    type=int,\n    help=\"Number of tasks to run\",\n)\n@click.argument(\"tag\")\ndef run(count, tag):\n    manager.run(tag=tag, count=count)\n\n\n@cli.command()\ndef dashboard():\n    manager.dashboard()\n\n\n@cli.command()\ndef ps():\n    manager.ps()\n\n\n@cli.command()\ndef get_results():\n    print(manager.get_results())\n\n\n@cli.command()\ndef clean():\n    manager.clean()\n\n\nif __name__ == \"__main__\":\n    cli()\n```\n\n### Getting results\n\n```py\nfrom redis import Redis\nfrom werkit.parallel import get_results\n\n\nget_results(wait_until_done=True, connection=Redis.from_url(...))\n```\n\n### Monitoring\n\nYou can monitor your queues using [RQ Dashboard][] or one of the\n[other methods outlined here][monitoring].\n\n[rq dashboard]: https://github.com/eoranged/rq-dashboard\n[monitoring]: https://python-rq.org/docs/monitoring/\n\n\n## Contribute\n\n- Issue Tracker: https://github.com/metabolize/werkit/issues\n- Source Code: https://github.com/metabolize/werkit\n\nPull requests welcome!\n\n\n## Support\n\nIf you are having issues, please let us know.\n\n\n## License\n\nThe project is licensed under the MIT License.",
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