{
    "info": {
        "author": "Alexandr Lispython",
        "author_email": "lispython@users.noreply.github.com",
        "bugtrack_url": null,
        "classifiers": [
            "Intended Audience :: Developers",
            "Intended Audience :: System Administrators",
            "Operating System :: OS Independent",
            "Operating System :: POSIX",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: Implementation :: CPython",
            "Topic :: Software Development",
            "Topic :: Software Development :: Libraries",
            "Topic :: System :: Monitoring",
            "Topic :: System :: Networking :: Monitoring"
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        "description": "Prometheus instrumentation library for Python applications\n============================================================\n\nThe unofficial Python 2 and 3 client for `Prometheus`_.\n\n.. image:: https://travis-ci.org/Lispython/pyprometheus.svg?branch=master\n    :target: https://travis-ci.org/Lispython/pyprometheus\n\n\n\nFeatures\n--------\n\n- Four types of metric are supported: Counter, Gauge, Summary(without quantiles) and Histogram.\n- InMemoryStorage (do not use it for multiprocessing apps)\n- UWSGI storage - share metrics between processes\n- UWAGI flush storage - sync metrics with uwsgi sharedarea by flush call\n- time decorator\n- time context manager\n\n\n\nINSTALLATION\n------------\n\nTo use pyprometheus use pip or easy_install:\n\n:code:`pip install pyprometheus`\n\nor\n\n:code:`easy_install pyprometheus`\n\n\nHOW TO INSTRUMENTING CODE\n-------------------------\n\nGauge\n~~~~~\n\nA gauge is a metric that represents a single numerical value that can arbitrarily go up and down.::\n\n   from pyprometheus import Gauge\n   from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n   storage = LocalMemoryStorage()\n   registry = CollectorRegistry(storage=storage)\n   gauge = Gauge(\"job_in_progress\", \"Description\", registry=registry)\n\n   gauge.inc(10)\n   gauge.dec(5)\n   gauge.set(21.1)\n\n\nutilities::\n\n  gauge.set_to_current_time()   # Set to current unixtime\n\n  # Increment when entered, decrement when exited.\n  @gauge.track_in_progress()\n  def f():\n      pass\n\n  with gauge.track_in_progress():\n      pass\n\n\n  with gauge.time():\n      time.sleep(10)\n\n\n\nCounter\n~~~~~~~\n\nA counter is a cumulative metric that represents a single numerical value that only ever goes up.::\n\n   from pyprometheus import Counter\n   from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n   storage = LocalMemoryStorage()\n   registry = CollectorRegistry(storage=storage)\n   counter = Counter(\"requests_total\", \"Description\", registry=registry)\n\n   counter.inc(10)\n\n\n\n\n\nSummary\n~~~~~~~\n\nSimilar to a histogram, a summary samples observations (usually things like request durations and response sizes).::\n\n   from pyprometheus import Summary\n   from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n   storage = LocalMemoryStorage()\n   registry = CollectorRegistry(storage=storage)\n   s = Summary(\"requests_duration_seconds\", \"Description\", registry=registry)\n\n   s.observe(0.100)\n\n\nutilities for timing code::\n\n   @gauge.time()\n   def func():\n      time.sleep(10)\n\n   with gauge.time():\n      time.sleep(10)\n\n\n\nHistogram\n~~~~~~~~~\n\nA histogram samples observations (usually things like request durations or response sizes) and counts them in configurable buckets. It also provides a sum of all observed values.::\n\n  from pyprometheus import Summary\n   from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n   storage = LocalMemoryStorage()\n   registry = CollectorRegistry(storage=storage)\n   histogram = Histogram(\"requests_duration_seconds\", \"Description\", registry=registry)\n\n   histogram.observe(1.1)\n\nutilities for timing code::\n\n   @histogram.time()\n   def func():\n      time.sleep(10)\n\n   with histogram.time():\n      time.sleep(10)\n\n\n\nLabels\n~~~~~~\n\nAll metrics can have labels, allowing grouping of related time series.\n\n\nExample::\n\n    from pyprometheus import Counter\n    c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint'])\n    c.labels('get', '/').inc()\n    c.labels('post', '/submit').inc()\n\nor labels as keyword arguments::\n\n    from pyprometheus import Counter\n    c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint'])\n    c.labels(method='get', endpoint='/').inc()\n    c.labels(method='post', endpoint='/submit').inc()\n\n\n\nSTORAGES\n--------\n\nCurrently library support 2 storages: LocalMemoryStorage and UWSGIStorage\n\nEvery registry MUST have link to storage::\n\n  from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n  storage = LocalMemoryStorage()\n  registry = CollectorRegistry(storage=storage)\n\n\nUse LocalMemoryStorage\n~~~~~~~~~~~~~~~~~~~~~~\n\nSimple storage that store samples to application memory. It can be used with threads.::\n\n  from pyprometheus import BaseRegistry, LocalMemoryStorage\n\n  storage = LocalMemoryStorag()\n\n\nUse UWSGIStorage\n~~~~~~~~~~~~~~~~\n\nUWSGIStorage allow to use `uwsgi sharedarea`_ to sync metrics between processes.::\n\n  from pyprometheus.contrib.uwsgi_features import UWSGICollector, UWSGIStorage\n\n  SHAREDAREA_ID = 0\n  storage = UWSGIStorage(SHAREDAREA_ID)\n\n\n\nalso need to configure UWSGI sharedaread pages.\n\n\n\n\nEXPORTING\n---------\n\nLibrary have some helpers to export metrics\n\nTo text format\n~~~~~~~~~~~~~~\n\nYou can convert registry to text format::\n\n\n  from pyprometheus import BaseRegistry, LocalMemoryStorage\n  from pyprometheus.utils.exposition import registry_to_text\n  from pyprometheus import Gauge\n\n  storage = LocalMemoryStorage()\n  registry = CollectorRegistry(storage=storage)\n  g = Gauge('raid_status', '1 if raid array is okay', registry=registry)\n  g.set(1)\n  print(registry_to_text(registry))\n\n\n\nText file export\n~~~~~~~~~~~~~~~~\n\nThis is useful for monitoring cronjobs, or for writing cronjobs to expose metrics about a machine system.::\n\n  from pyprometheus import BaseRegistry, LocalMemoryStorage\n  from pyprometheus.utils.exposition import registry_to_text, write_to_textfile\n  from pyprometheus import Gauge\n\n  storage = LocalMemoryStorage()\n  registry = CollectorRegistry(storage=storage)\n  g = Gauge('raid_status', '1 if raid array is okay', registry=registry)\n  g.set(1)\n  write_to_textfile(registry, \"/path/to/file/metrics.prom\")\n\n\nYou can configure `text file collector`_ to use generated file.\n\n\nTODO\n----\n\nSome features that we plan to do:\n\n- [ ] Add mmap storage\n- [ ] Add features for async frameworks\n- [ ] Optimize UWSGI storage byte pad\n- [ ] Add quantiles\n\n\n\nEXAMPLE PROJECT\n---------------\n\nWe create `example project`_ to show hot to use pyprometheus in real project.\n\n\nCONTRIBUTE\n----------\n\nFork https://github.com/Lispython/pyprometheus/ , create commit and pull request to ``develop``.\n\n\n\n.. _`example project`: http://github.com/Lispython/pyprometheus_demo\n.. _`text file collector`: https://github.com/prometheus/node_exporter#textfile-collector\n.. _`uwsgi sharedarea`: http://uwsgi-docs.readthedocs.io/en/latest/SharedArea.html\n.. _`Prometheus`: http://prometheus.io\n\n\n",
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