{
    "info": {
        "author": "hampsterx",
        "author_email": "tim.vdh@gmail.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
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        "description": "# async-kinesis\n\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black) [![PyPI version](https://badge.fury.io/py/async-kinesis.svg)](https://badge.fury.io/py/async-kinesis) [![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/) [![Python 3.6](https://img.shields.io/badge/python-3.7-blue.svg)](https://www.python.org/downloads/release/python-370/)\n\n```\npip install async-kinesis\n```\n\n## Features\n\n- uses queues for both producer and consumer\n  - producer flushes with put_records() if has enough to flush or after \"buffer_time\" reached\n  - consumer iterates over msg queue independent of shard readers\n- Configurable to handle Sharding limits but will throttle/retry if required\n  - ie multiple independent clients are saturating the Shards\n- Checkpointing with heartbeats\n  - deadlock + reallocation of shards if checkpoint fails to heartbeat within \"session_timeout\"\n- processors (aggregator + serializer)\n    - json line delimited, msgpack\n\n\nSee [docs/design](./docs/DESIGN.md) for more details.\nSee [docs/yetanother](docs/YETANOTHER.md) as to why reinvent the wheel.\n\n## Environment Variables\n\nAs required by boto3\n\n```\nAWS_ACCESS_KEY_ID\nAWS_SECRET_ACCESS_KEY\n```\n\n## Producer\n\n    from kinesis import Producer\n\n    async with Producer(stream_name=\"test\") as producer:\n        # Put item onto queue to be flushed via put_records()\n        await producer.put({'my': 'data'})\n\n\nOptions:\n\n(comments in quotes are Kinesis Limits as per AWS Docs)\n\n| Arg | Default | Description |\n| --- | --- | --- |\n| region_name | None | AWS Region |\n| buffer_time | 0.5 | Buffer time in seconds before auto flushing records |\n| put_rate_limit_per_shard | 1000 | \"A single shard can ingest up to 1 MiB of data per second (including partition keys) or 1,000 records per second for writes\" |\n| put_bandwidth_limit_per_shard | 1024 | Kb per sec. max is 1024 per shard (ie 1 MiB). Keep below to minimize ProvisionedThroughputExceeded\" errors |\n| batch_size | 500 | \"Each PutRecords request can support up to 500 records\" |\n| max_queue_size | 10000 | put() method will block when queue is at max |\n| after_flush_fun | None | async function to call after doing a flush (err put_records()) call |\n| processor | JsonProcessor() | Record aggregator/serializer. Default is JSON without aggregation. Note this is highly inefficient as each record can be up to 1Mib |\n\n\n## Consumer\n\n    from kinesis import Consumer\n\n    async with Consumer(stream_name=\"test\") as consumer:\n        while True:\n            async for item in consumer:\n                print(item)\n            # caught up.. take a breather~\n\n\nOptions:\n\n(comments in quotes are Kinesis Limits as per AWS Docs)\n\n\n| Arg | Default | Description |\n| --- | --- | --- |\n| region_name | None | AWS Region |\n| max_queue_size | 10000 | the fetch() task shard will block when queue is at max |\n| max_shard_consumers | None | Max number of shards to use. None = all |\n| record_limit | 10000 | Number of records to fetch with get_records() |\n| sleep_time_no_records | 2 | No of seconds to sleep when caught up |\n| iterator_type | TRIM_HORIZON | Default shard iterator type for new/unknown shards (ie start from start of stream). Alternative is \"LATEST\" (ie end of stream) |\n| shard_fetch_rate | 1 | No of fetches per second (max = 5). 1 is recommended as allows having multiple consumers without hitting the max limit. |\n| checkpointer | MemoryCheckPointer() | Checkpointer to use |\n| processor | JsonProcessor() |  Record aggregator/serializer. Must Match processor used by Producer() |\n\n\n## Checkpointers\n\n- memory (the default but kinda pointless)\n\n```\n    MemoryCheckPointer()\n```\n\n- redis\n\n```\n    RedisCheckPointer(name, session_timeout=60, heartbeat_frequency=15, is_cluster=False)\n```\n\nRequires ENV:\n\n```\n    REDIS_HOST\n```\n\nRequires `pip install aredis`\n\n\n## Processors (Aggregator + Serializer)\n\n\nAggregation enable batching up multiple records to more efficiently use the stream.\nRefer https://aws.amazon.com/blogs/big-data/implementing-efficient-and-reliable-producers-with-the-amazon-kinesis-producer-library/\n\n\n| Class | Aggregator | Serializer | Description |\n| --- | --- | --- | --- |\n| StringProcessor | SimpleAggregator | StringSerializer | Single String record |\n| JsonProcessor | SimpleAggregator | JsonSerializer | Single JSON record |\n| JsonLineProcessor | NewlineAggregator | JsonSerializer | Multiple JSON record separated by new line char |\n| MsgpackProcessor | NetstringAggregator | MsgpackSerializer | Multiple Msgpack record framed with Netstring Protocol (https://en.wikipedia.org/wiki/Netstring) |\n\nNote you can define your own processor easily as it's simply a class inheriting the Aggregator + Serializer.\n\n```\nclass MsgpackProcessor(Processor, NetstringAggregator, MsgpackSerializer):\n    pass\n```\n\nJust define a new Serializer class with serialize() and deserialize() methods.\n\nNote:\n\n* Json will use `pip install ujson` if installed\n* Msgpack requires `pip install msgpack` to be install \n\n\n## Benchmark/Example\n\nSee [benchmark.py](./benchmark.py) for code\n\n50k items of approx 1k (python) in size, using single shard.\n\n![Benchmark](docs/benchmark.png)\n\n\n## Unit Testing\n\nUses https://github.com/mhart/kinesalite for local testing.\n\nRun tests via docker\n\n```\ndocker-compose up --abort-on-container-exit --exit-code-from test\n```\n\nFor local testing use\n\n```\ndocker-compose up kinesis redis\n```\n\nthen within your virtualenv\n\n```\nnosetests\n\n# or run individual test\nnosetests tests.py:KinesisTests.test_create_stream_shard_limit_exceeded\n```\n\nNote there are a few test cases using the *actual* AWS Kinesis (AWSKinesisTests)\nThese require setting an env in order to run\n\nCreate an \".env\" file with\n\n```\nTESTING_USE_AWS_KINESIS=1\n```\n\nNote you can ignore these tests if submitting PR unless core batching/processing behaviour is being changed.\n\n\n\n\n",
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