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        "description": "logcollect\n==========\n\nPython library for centralized log collecting\n\nProvides simple configuration for collecting python logs to ELK stack\nvia RabbitMQ.\n\nSupported message flow is following:\n\n::\n\n\n    python.logging\n          ||\n          \\/\n      logcollect\n          ||\n          \\/\n       RabbitMQ  \n          ||\n          \\/\n       Logstash\n          ||\n          \\/\n     ElasticSearch\n          ||\n          \\/\n        Kibana\n\nMechanics\n---------\n\nNative logging\n~~~~~~~~~~~~~~\n\n``logcollect.boot.default_config`` ensures that root logger has\ncorrectly configured amqp handler.\n\nDjango\n~~~~~~\n\n``logcollect.boot.django_dict_config`` modifies\n``django.conf.settings.LOGGING`` to ensure correct amqp handler for root\nlogger. It should be called in settings module after LOGGING definition.\n\nCelery\n~~~~~~\n\n``logcollect.boot.celery_config`` adds signal handler for\n``worker_process_init`` signal, and after that adds amqp handler to\n``task_logger`` base handler. If necessary, root logger can be also\nattached to amqp handler.\n\nTips for configuration\n----------------------\n\nLogstash\n~~~~~~~~\n\n.. code:: ruby\n\n\n    input {\n      rabbitmq {\n        exchange => \"logstash\"\n        queue => \"logstash\"\n        host => \"rabbitmq-host\"\n        type => \"amqp\"\n        durable => true\n        codec => \"json\"\n      }\n    }\n    output {\n      elasticsearch { host => localhost }\n      stdout { codec => rubydebug }\n    }\n\nlogcollect\n~~~~~~~~~~\n\nAll boot helpers have same parameters:\n\n-  broker\\_uri - celery-style RabbitMQ connection string, i.e.\n   ``amqp://guest@localhost//vhost``\n-  exchange, routing\\_key - message routing info for RabbitMQ\n-  durable - message delivery mode\n-  level - handler loglevel\n-  activity\\_identity - dict with \"process type info\"\n\nActivity Identity\n~~~~~~~~~~~~~~~~~\n\nAssuming we deployed two projects on same host: \"github\" and \"jenkins\".\nBoth have web backends and background workers. Activity identity helps\nto identify messages from these workers:\n\n+-----------+--------------+-----------------------------------------------------------+\n| Project   | Worker       | Activity identity                                         |\n+===========+==============+===========================================================+\n| github    | backend      | ``{\"project\": \"github\", \"application\": \"backend\"}``       |\n+-----------+--------------+-----------------------------------------------------------+\n| jenkins   | background   | ``{\"project\": \"jenkins\", \"application\": \"background\"}``   |\n+-----------+--------------+-----------------------------------------------------------+\n\n``loggername`` could be used for separating different parts of code\nwithin a worker. Hostnames and process PIDs are added automatically.\n\nCorrelation ID\n~~~~~~~~~~~~~~\n\nNot supported yet, but idea is marking log messages about same object\nwith ID information about this object.\n\nExamples\n--------\n\nNative python logging\n~~~~~~~~~~~~~~~~~~~~~\n\n.. code:: sh\n\n     python test_native/native_logging.py\n\nDjango\n~~~~~~\n\n.. code:: sh\n\n     python test_django/manage.py test_log\n\nCelery\n~~~~~~\n\nFirst, start worker:\n\n.. code:: sh\n\n    celery worker -A test_celery.app.celery\n\nThen send a task to that worker:\n\n.. code:: sh\n\n    python test_celery/send_task.py\n\nRelated works\n-------------\n\nAMQPHandler and AMQPLogstashFormatter are copied from\n`python-logstash <https://github.com/vklochan/python-logstash>`__.\n\nSee also: \\* `RabbitMQ <https://github.com/rabbitmq/rabbitmq-server>`__\n\\* `Logstash <https://github.com/elastic/logstash>`__ \\*\n`Kibana <https://github.com/elastic/kibana>`__ \\*\n`Django <https://github.com/django/django>`__ \\*\n`Celery <https://github.com/celery/celery>`__",
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