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    "info": {
        "author": "Bojan Keca",
        "author_email": "kecabojan@gmail.com",
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            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
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        "description": "# cloudwatch-metrics-buffer ![Python 3](https://img.shields.io/badge/Python-3-brightgreen.svg)\n\nThis is a wrapper library for publishing metrics to **[AWS CloudWatch](https://aws.amazon.com/cloudwatch/)**. \n\nWhile playing around with lambdas and serveless frameworks, I needed a library to help me with publishing metrics to CloudWatch in easy and elegant way. I wanted to avoid boilerplate code that polutes all my methods. Ideally, I would decorate my function to measure execution time or count. After unsuccessful search, I implemented my own.\n\nThis wrapper will buffer metrics first, then send them in batches. It supports **timeit** and **count** decorators for metricating functions in elegant way. Though publishing metrics is batched, there is no guaranty ClouWatch will swallow everything. If you send > [150 TPS](https://docs.aws.amazon.com/en_pv/AmazonCloudWatch/latest/APIReference/API_PutMetricData.html) \n(can happen easily if you scale out with Lambdas), you might get throttled. Read CloudWatch documentation for limits and pricing consideration.\n\n## Installation\n```\npip install cloudwatch-metrics-buffer\n```\n\n## Usage\n### Post metrics explicitly\n```python\nfrom cwmetrics import CloudWatchMetricsBuffer\n\ncw = CloudWatchMetricsBuffer('Some Namespace')\n\n# buffer single metrics value to buffer\ncw.put_value('total_calls', 5) # metric without units of value 5\ncw.put_value('latency', 11.25, unit='Milliseconds') # metric with unit specified\ncw.put_value('latency', 11.25, dimensions={'HTTP Method': 'GET'}, unit='Milliseconds') # same latency with specified dimension \ncw.put_value('home-page', 1, timestamp=datetime.datetime(2019, 10, 10, 14, 0, 0)) # metric on exact time\n\n# buffer statistic value; use this if you are gathering your statistics along the way in your app\ncw.put_statistic('metric', sample_count=50, sum=10000, minimum=0, maximum=500)\n\n# send all to Cloudwatch\ncw.send()\n```\n\n### Post metrics using decorators\n```python\nfrom cwmetrics import CloudWatchMetricsBuffer\n\ncw = CloudWatchMetricsBuffer('Some Namespace')\n\n# send value of for metric for each execution\n@cw.count('count_metric1')\ndef func():\n   ...\n\nfunc()\n```\n\nYou can also decorate function multiple times. Publishing to CloudWatch is executed after outer decorator finishes:\n```python\n# measure execution time in milliseconds and count request\n@cw.timeit('api')\n@cw.timeit('api', dimensions={'HTTP Method': 'GET'})\n@cw.count('requests', dimensions={'HTTP Method': 'GET'})\ndef process_api_request():\n   ...\n\n# CW will receive 3 metric values\nprocess_api_request() \n```\n\nThis will also work:\n```python\n@cw.timeit('api')\n@cw.timeit('api', dimensions={'HTTP Method': 'GET'})\n@cw.count('requests', dimensions={'HTTP Method': 'GET'})\n@cw.count('requests')\ndef process_api_request():\n    ...\n    authenticate()\n    ...\n\n@cw.timeit('auth')\n@cw.count('auth requests')\ndef authenticate():\n    ...\n\n# all metrics (total of 6) are buffered and sent after method was executed\nprocess_api_request() \n```\n\n\n",
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        "license": "MIT",
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        "name": "cloudwatch-metrics-buffer",
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