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    "info": {
        "author": "Jens Nistler <opensource@jensnistler.de>, Bogdan Radko <bogdan.radko@regiohelden.de>",
        "author_email": "opensource@regiohelden.de",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries :: Python Modules",
            "Topic :: System :: Monitoring"
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        "description": "[![PyPI version](https://badge.fury.io/py/django-datawatch.svg)](https://badge.fury.io/py/django-datawatch)\n[![Travis CI build status](https://travis-ci.org/RegioHelden/django-datawatch.svg)](https://travis-ci.org/RegioHelden/django-datawatch)\n[![Coverage Status](https://coveralls.io/repos/github/RegioHelden/django-datawatch/badge.svg?branch=add_coveralls)](https://coveralls.io/github/RegioHelden/django-datawatch?branch=add_coveralls)\n[![Open Source Love](https://badges.frapsoft.com/os/v2/open-source.svg?v=103)](https://github.com/ellerbrock/open-source-badges/)\n[![MIT Licence](https://badges.frapsoft.com/os/mit/mit.svg?v=103)](https://opensource.org/licenses/mit-license.php)\n\n# Django Datawatch\n\nWith Django Datawatch you are able to implement arbitrary checks on data, review their status and even describe what to do to resolve them.\nThink of [nagios](https://www.nagios.org/)/[icinga](https://www.icinga.org/) for data.\n\n## Check execution backends\n\n### Synchronous\n\nWill execute all tasks synchronously which is not recommended but the most simple way to get started.\n\n### Celery\n\nWill execute the tasks asynchronously using celery as a task broker and executor.\nCelery is supported from 3.1.25.\n\n### Other backends\n\nFeel free to implement other task execution backends and send a pull request.\n\n## Install\n\n```shell\n$ pip install django-datawatch\n```\n\nAdd `django_datawatch` to your `INSTALLED_APPS`\n\n## Celery beat database scheduler\n\nIf the datawatch scheduler should be run using the celery beat database scheduler, you need to install [django_celery_beat](hhttp://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html#beat-custom-schedulers) for celery >= 4 or [django-celery](https://github.com/celery/django-celery) for celery < 4.\n\nAdd `django_datawatch.tasks.django_datawatch_scheduler` to the `CELERYBEAT_SCHEDULE` of your app.\nThis task should be executed every minute e.g. `crontab(minute='*/1')`, see example app.\n\n## Write a custom check\n\nCreate `checks.py` inside your module.\n\n```python\nfrom datetime import datetime\n\nfrom celery.schedules import crontab\n\nfrom django_datawatch.datawatch import datawatch\nfrom django_datawatch.base import BaseCheck, CheckResponse\nfrom django_datawatch.models import Result\n\n\n@datawatch.register\nclass CheckTime(BaseCheck):\n    run_every = crontab(minute='*/5')  # scheduler will execute this check every 5 minutes\n\n    def generate(self):\n        yield datetime.now()\n\n    def check(self, payload):\n        response = CheckResponse()\n        if payload.hour <= 7:\n            response.set_status(Result.STATUS.ok)\n        elif payload.hour <= 12:\n            response.set_status(Result.STATUS.warning)\n        else:\n            response.set_status(Result.STATUS.critical)\n        return response\n\n    def get_identifier(self, payload):\n        # payload will be our datetime object that we are getting from generate method\n        return payload\n\n    def get_payload(self, identifier):\n        # as get_identifier returns the object we don't need to process it\n        # we can return identifier directly\n        return identifier\n```\n\n### .generate\n\nMust yield payloads to be checked. The check method will then be called for every payload.\n\n### .check\n\nMust return an instance of CheckResponse.\n\n### .get_identifier\n\nMust return a unique identifier for the payload. \n\n### trigger check updates\n\nCheck updates for individual payloads can also be triggered when related datasets are changed.\nThe map for update triggers is defined in the Check class' trigger_update attribute.\n\n```\ntrigger_update = dict(subproduct=models_customer.SubProduct)\n```\n\nThe key is a slug to define your trigger while the value is the model that issues the trigger when saved.\nYou must implement a resolver function for each entry with the name of get_<slug>_payload which returns the payload to check (same datatype as .check would expect or .generate would yield).\n```\ndef get_subproduct_payload(self, instance):\n    return instance.product\n```\n\n## Run your checks\n\nA management command is provided to queue the execution of all checks based on their schedule.\nAdd a crontab to run this command every minute and it will check if there's something to do.\n\n```shell\n$ ./manage.py datawatch_run_checks\n$ ./manage.py datawatch_run_checks --slug=example.checks.UserHasEnoughBalance\n```\n\n## Refresh your check results\n\nA management command is provided to forcefully refresh all existing results for a check.\nThis comes in handy if you changes the logic of your check and don't want to wait until the periodic execution or an update trigger.\n\n```shell\n$ ./manage.py datawatch_refresh_results\n$ ./manage.py datawatch_refresh_results --slug=example.checks.UserHasEnoughBalance\n```\n\n## Get a list of registered checks\n\n```shell\n$ ./manage.py datawatch_list_checks\n```\n\n## Clean up your database\n\nRemove the unnecessary check results and executions if you've removed the code for a check.\n\n```shell\n$ ./manage.py datawatch_clean_up\n```\n\n## Settings\n\n```python\nDJANGO_DATAWATCH_BACKEND = 'django_datawatch.backends.synchronous'\nDJANGO_DATAWATCH_RUN_SIGNALS = True\n```\n\n### DJANGO_DATAWATCH_BACKEND\n\nYou can chose the backend to run the tasks. Supported are 'django_datawatch.backends.synchronous' and 'django_datawatch.backends.celery'.\n\nDefault: 'django_datawatch.backends.synchronous'\n\n### DJANGO_DATAWATCH_RUN_SIGNALS\n\nUse this setting to disable running post_save updates during unittests if required.\n\nDefault: True\n\n### celery task queue\n\nDatawatch supported setting a specific queue in release < 0.4.0\n\nWith the switch to celery 4, you should use task routing to define the queue for your tasks, see http://docs.celeryproject.org/en/latest/userguide/routing.html\n\n# CONTRIBUTE\n\n## Dev environment\n- docker (at least 17.12.0+)\n- docker-compose (at least 1.18.0)\n- docker-hostmanager\n\n## docker-hostmanager\n\nIn order to access the application on your browser, your host machine must be able to resolve the host name of your container.\nWe're using docker-hostmanager to manage the hosts file entries.\n\nLinux:\n\n```\n$ docker run -d --name docker-hostmanager --restart=always -v /var/run/docker.sock:/var/run/docker.sock -v /etc/hosts:/hosts iamluc/docker-hostmanager\n```\n\nFor other environments, see https://github.com/iamluc/docker-hostmanager\n\n## Setup\n\nWe've included an example app to show how django_datawatch works.\nStart by launching the included docker container.\n```bash\ndocker-compose up -d\n```\n\nThen setup the example app environment.\n```bash\ndocker-compose run --rm django migrate\ndocker-compose run --rm django loaddata example\n```\nThe installed superuser is \"example\" with password \"datawatch\".\n\n## Run checks\n\nLogin on the admin interface and open http://datawatch.rh-dev.eu:8000/ afterwards.\nYou'll be prompted with an empty dashboard. That's because we didn't run any checks yet.\nLet's enqueue an update.\n```bash\ndocker-compose run --rm django datawatch_run_checks --force\n```\n\nThe checks for the example app are run synchronously and should be updated immediately.\nIf you decide to switch to the celery backend, you should now start a celery worker to process the checks.\n```bash\ndocker-compose run --rm --entrypoint=celery django worker -A example -l DEBUG\n```\n\nTo execute the celery beat scheduler which runs the datawatch scheduler every minute, just run:\n```bash\ndocker-compose run --rm --entrypoint=celery django beat --scheduler django_celery_beat.schedulers:DatabaseScheduler -A example\n```\n\nYou will see some failed check now after you refreshed the dashboard view.\n\n![Django Datawatch dashboard](http://static.jensnistler.de/django_datawatch.png \"Django Datawatch dashboard\")\n\n## Run the tests\n```bash\ndocker-compose run --rm django test\n```\n\n## Making a new release\n\n[bumpversion](https://github.com/peritus/bumpversion) is used to manage releases.\n\nAdd your changes to the [CHANGELOG](./CHANGELOG.rst), run\n```bash\ndocker-compose run django bumpversion <major|minor|patch>\n```\nthen push (including tags).",
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