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        "author": "Like Zhang",
        "author_email": "zlike@yahoo.com",
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        "description": "# cocotask\n### Build task queue on either Rabbitmq, Kafka or Redis! Simple! Easy! and FAST!!!!\n\n**Why creating this framework?**\n* Most task queues using Rabbitmq/Kafka/Redis are doing the same thing, but there is no unified wrapper. It's a waste of time to write code for different MQs if all you need is a task queue to distribute jobs\n* No need to worry about using Rabbitmq, Kafka or Redis. Just pick one and go! It's simply a few lines of config changes in future if you want to switch to a different underlying system\n* Hide all details for connecting/subscribing/publishing/etc. You can just use the same API for any of Kafka/Rabbitmq/Redis!\n* Minimize the efforts for team members to handcraft the code for exchange/queue handling\n* Team members should focus on how to handle messages\n* There lacks good mananger tool/lib to handle creating multiple consumers (although it's simple)\n* Celery is the original idea, but it doesn't support Kafka and Windows platform. It's also tightly coupled with Python alone.\n<hr>\n\n## Test\n\n1. install rabbitmq or kafka on local machine (either docker or pure rabbitmq).\n   - Rabbitmq: https://www.rabbitmq.com/\n   - Kafka: https://kafka.apache.org/quickstart  (for kafka, you have to manually create a topic named `test_topic_1` in order to run the test. In order to try multiple consumers, you need to set partitions to 2 or above, not 1)\n   - Redis: https://redis.io/download\n\n2. make sure it's running Python 3.5 above\n\n3. pip install pika kafka-python redis jsmin\n\n4. pip install cocotask\n\n5. now you have cocotask setup on your machine. To test, you can go to the ./test folder\n   - Run: `python producer_test.py`   (this will post a string. Code is very simple)\n   - In another window, under ./test, run:  **`cocotask ./config.json userworkers TestWorker 4`**\n     you'll see the worker starts and process 1 message we just posted.\n\n6. So the key part is how we use cocotask command tool. the parameters are:\n   - config_path: path to config file\n   - module_name: module of your customized worker class\n   - class_name: the class name of your own worker class (in the example above, it's userworkers.TestWorker, so the module name is userworkers, the class name is TestWorker)\n   - number of workers: the total number of customer workers\n   - logginglevel(optional): python logging level INFO/DEBUG/etc.\n   - modulepath(optional): the relative path to find the module you defined. Default is '.'\n\n7. Develop your own worker class and try\n\n## Development\n\n**Build your own worker**\n\n```\nfrom cocotask import CocoBaseWorker\n\nclass TestWorker(CocoBaseWorker):\n\n    def process(self, body):\n        print(body)\n```\nCheck userworkers/test_worker.py for reference.\n\n**Post a message**\n```\nfrom cocotask import CocoProducerManager as pm\nimport json\n\nwith open('config.json', 'r') as f:\n    config = json.load(f)\n\nproducer = pm.create_instance(config)\n\nproducer.connect()\nproducer.send('12345678')\nproducer.close()\n```\n**Switch from RabbitMQ to Kafka or reverse**\nIn test/config.json\n```\n{\n    \"MQ_TYPE\": \"RMQ\",  # change this to KAFKA if your underlying MQ is KAFKA\n\n    \"RMQ\": {\n        ...\n    },\n\n    \"KAFKA\": {\n        ...\n    },\n\n    \"REDIS\": {\n        ...\n    }\n}\n\n```\n**We do support SASL_PLAINTEXT for kafka and simple auth in Redis as in the comments of the config file. Check their website to see how to setup the authentication**\n\nYou can build your own dictionary object as configuration for sure, as long as it contains the required fields.\n\n\nThat's it. Simple and straightforward.\n\n\n",
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        "keywords": "task message queue MQ Pika kafka-python rabbitmq kafka redis rmq producer consumer celery",
        "license": "MIT",
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        "name": "cocotask",
        "package_url": "https://pypi.org/project/cocotask/",
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