mirror of https://github.com/zulip/zulip.git
135 lines
4.8 KiB
Python
Executable File
135 lines
4.8 KiB
Python
Executable File
#!/usr/bin/env python
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#
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# Generates % delta activity metrics from graphite/statsd data
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#
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import os, sys
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
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import optparse
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from itertools import dropwhile, takewhile
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from datetime import timedelta, datetime
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from zephyr.lib.timestamp import datetime_to_timestamp
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from zephyr.lib.utils import statsd_key
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import requests
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# Workaround to support the Python-requests 1.0 transition of .json
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# from a property to a function
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requests_json_is_function = callable(requests.Response.json)
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def extract_json_response(resp):
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if requests_json_is_function:
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return resp.json()
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else:
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return resp.json
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def get_data(url, username, pw):
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from requests.auth import HTTPDigestAuth
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res = requests.get(url, auth=HTTPDigestAuth(username, pw), verify=False)
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if res.status_code != 200:
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print "Failed to fetch data url: %s" % (res.error,)
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return []
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return extract_json_response(res)
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def noon_of(day=datetime.now()):
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return datetime(year=day.year, month=day.month, day=day.day, hour=12)
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def points_during_day(data, noon):
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"""Returns all the points in the dataset that occur in the 12 hours around
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the datetime object that is passed in. data must be sorted."""
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before =datetime_to_timestamp(noon - timedelta(hours=12))
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after = datetime_to_timestamp(noon + timedelta(hours=12))
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between = filter(lambda pt: pt[1] > before and pt[1] < after, data)
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return between
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def best_during_day(data, day):
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valid = sorted(points_during_day(data, day), key=lambda pt: pt[0], reverse=True)
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if len(valid):
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return valid[0][0]
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else:
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return None
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def percent_diff(prev, cur):
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if prev is None or cur is None:
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return None
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return ((cur - prev) / prev) * 100
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def parse_data(data, today):
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for metric in data:
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# print "Got %s with data points %s" % (metric['target'], len(metric['datapoints']))
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if metric['target'] in statsd_targets:
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# Calculate % between peak 2hr and 10min across each day and week
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metric['datapoints'].sort(key=lambda p: p[1])
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print "\nUsers active in %s span:\n" % (metric['target'].split('.')[-1],)
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best_today = best_during_day(metric['datapoints'], today)
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for i in xrange(1, 100):
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day = today - timedelta(days=i)
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week = today - timedelta(weeks=i*7)
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# Ignore weekends
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if day.weekday() not in [5, 6]:
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best = best_during_day(metric['datapoints'], day)
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if best is not None:
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print "Change between today and last %s, %s days ago:\t%.02f%%\t\t(%.01f to %.01f users)" \
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% (day.strftime("%A"), i, percent_diff(best, best_today), best, best_today)
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best = best_during_day(metric['datapoints'], week)
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if best is not None:
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print "Weekly %% change from %s weeks ago today:\t\t%.02f" \
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% (i, percent_diff(best, best_today))
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parser = optparse.OptionParser(r"""
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%prog --user username --password pw [--start-from unixtimestamp]
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Generates activity statistics with detailed week-over-week percentage change
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""")
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parser.add_option('--user',
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help='Graphite usernarme',
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metavar='USER')
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parser.add_option('--password',
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help='Graphite password',
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metavar='PASSWORD')
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parser.add_option('--start-from',
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help='What day to consider as \'today\' when calculating stats as a Unix timestamp',
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metavar='STARTDATE',
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default='today')
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parser.add_option('--realm',
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help='Which realm to query',
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default='all')
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if __name__ == '__main__':
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(options, args) = parser.parse_args()
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if not options.user or not options.password:
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parser.error("You must enter a username and password to log into graphite with")
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startfrom = noon_of(day=datetime.now())
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if options.start_from != 'today':
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startfrom = noon_of(day=datetime.fromtimestamp(int(options.start_from)))
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print "Using baseline of today as %s" % (startfrom,)
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realm_key = statsd_key(options.realm, True)
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buckets = ["12hr", "2hr", "0_16hr"]
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# This is the slightly-cleaned up JSON api version of https://graphiti.humbughq.com/graphs/945c7aafc2d
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#
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# Fetches 1 month worth of data
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DATA_URL="https://graphite.humbughq.com/render/?from=-28d&format=json"
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statsd_targets = ["stats.gauges.staging.users.active.%s.%s" % (realm_key, bucket) for bucket in buckets]
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for target in statsd_targets:
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DATA_URL += "&target=%s" % (target,)
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data = get_data(DATA_URL, options.user, options.password)
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parse_data(data, startfrom)
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