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    "info": {
        "author": "Mark Story",
        "author_email": "markstory@freshbooks.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7"
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        "description": "# Statsdecor\n\n[![Software License](https://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat-square)](LICENSE.txt)\n[![Build Status](https://api.travis-ci.org/freshbooks/statsdecor.svg)](https://travis-ci.org/freshbooks/statsdecor)\n\nA set of decorators and helper methods for adding statsd metrics to applications.\n\n## Installation\n\nYou can use pip to install statsdecor:\n\n```shell\npip install statsdecor\n```\n\n## Configuration\n\nYou must use `statsdecor.configure` to configure the internal statsd client before\ncalling other methods:\n\n```python\nimport statsdecor\n\nstatsdecor.configure(host='localhost', prefix='superapp.')\n```\n\nConfiguration is generally setup during your application's bootstrap. Once\nset configuration values are re-used in all clients that `statsdecor` creates.\n\n\n## Usage\n\nYou can track metrics with either the module functions, or decorators. Incrementing\nand decrementing counters looks like:\n\n### Metric functions\n\n```python\nimport statsdecor\n\nstatsdecor.incr('save.succeeded')\nstatsdecor.decr('attempts.remaining')\nstatsdecor.gauge('sessions.active', 9001)\n```\n\nCounters and timers can also be set through decorators:\n\n```python\nimport statsdecor.decorators as stats\n\n@stats.increment('save.succeeded')\ndef save(self):\n    pass\n\n@stats.decrement('attempts.remaining')\ndef attempt():\n    pass\n\n@stats.timed('api_request.duration')\ndef perform_request(self, req)\n    pass\n```\n\nWhen using decorators, metrics are only tracked if the decorated function\ndoes not raise an error.\n\n### Context\n\nStatsdecor includes a context manager that can help measure latency and volume\nwhile using metric tags to classify their success & failure.  For example,\nsuppose you are making a call to a remote service and wish to write a wrapper\nthat collects latency, volume and failure metrics.\n\nWith our knowledge about how the client library indicates errors we can make a context manager\nbased on StatsContext:\n\n```\nfrom statsdecor.context import StatsContext\n\nclass FoobarClientMetrics(StatsContext):\n    def __init__(self, tags=None):\n        tags = list(tags or [])\n        tags += ['caller:example_1']\n        super(ThingyStatsContext, self).__self__('thingy_client', tags=tags)\n\n    def exit_hook(self, exc_type, exc_val, exc_tb):\n        if exc_val is not None:\n            self.add_tags('result:failure')\n        else:\n            self.add_tags('result:success')\n\n        # Bonus: since we have the exception, classify the error type\n        if isinstance(exc_val, PermissionDenied):\n            self.add_tags('error:permissiondenied')\n        elif isinstance(exc_val, TimeOut):\n            self.add_tags('error:timeout')\n        elif exc_val is not None:\n            self.add_tags('error:exception')\n\n```\n\nNow writing wrapper functions with metrics is simple:\n\n```\ndef foobar_get_clients(**args):\n    with FoobarClientMetrics(tags=['method:get_clients']) as stats:\n        result = call_foobar_get_client(**args)\n\n        # We know all foo methods return result['status_code'] so let's\n        # add a status_code tag!\n        stats.add_tags('status_code:{}'.format(result[\"status_code\"]'))\n        return result\n\ndef foobar_add_client(**args):\n    with FoobarClientMetrics(tags=['method:add_client']) as stats:\n        result = call_foobar_add_client(**args)\n        stats.add_tags('status_code:{}'.format(result[\"status_code\"]'))\n        return result\n```\n\nNow we can graph:\n\n* volume of calls grouped by the `method` tag\n* average response time, excluding errors (timeouts will no longer skew the average)\n* volume of errors grouped by method, and/or type\n\n# Development\n\n## Testing and coverage\n\n```\nmake test\nmake coverage\n```\n\nYou can track metrics with either the module functions, or decorators. Incrementing\n\n## Releasing\n\nstatsdecor uses [semver](https://semver.org) for version numbers. Before tagging,\ncheck for all changes since the last tag for breaking changes, new features,\nand/or bugfixes.\n\n1. edit VERSION\n2. commit/pr/merge bump to VERSION\n3. `make tag`\n\n\n\n\n\n\n",
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