def test_milestone_ranges(self):
numbers = get_milestone_range("XS", "SM")
self.assertEqual(numbers[0], 1e1)
self.assertEqual(numbers[-1], 5e4)
def test_milestone_ranges(self):
numbers = get_milestone_range('XS', 'SM')
self.assertEqual(numbers[0], 1e1)
self.assertEqual(numbers[-1], 5e4)
class LoggingMixin(object):
"""Log requests to Redis
This draws inspiration from the code that can be found at: https://github.com/aschn/drf-tracking/blob/master/rest_framework_tracking/mixins.py
The big distinctions, however, are that this code uses Redis for greater
speed, and that it logs significantly less information.
We want to know:
- How many queries in last X days, total?
- How many queries ever, total?
- How many queries total made by user X?
- How many queries per day made by user X?
"""
milestones = get_milestone_range('SM', 'XXXL')
def initial(self, request, *args, **kwargs):
super(LoggingMixin, self).initial(request, *args, **kwargs)
d = date.today().isoformat()
user = request.user
endpoint = request.resolver_match.url_name
r = redis.StrictRedis(
host=settings.REDIS_HOST,
port=settings.REDIS_PORT,
db=settings.REDIS_DATABASES['STATS'],
)
pipe = r.pipeline()
# Global and daily tallies for all URLs.
pipe.incr('api:v3.count')
pipe.incr('api:v3.d:%s.count' % d)
# Use a sorted set to store the user stats, with the score representing
# the number of queries the user made total or on a given day.
pipe.zincrby('api:v3.user.counts', user.pk)
pipe.zincrby('api:v3.user.d:%s.counts' % d, user.pk)
# Use a sorted set to store all the endpoints with score representing
# the number of queries the endpoint received total or on a given day.
pipe.zincrby('api:v3.endpoint.counts', endpoint)
pipe.zincrby('api:v3.endpoint.d:%s.counts' % d, endpoint)
results = pipe.execute()
total_count = results[0]
user_count = results[2]
if total_count in MILESTONES_FLAT:
Event.objects.create(
description="API has logged %s total requests." % total_count)
if user.is_authenticated():
if user_count in self.milestones:
Event.objects.create(
description="User '%s' has placed their %s API request." %
(user.username, intcomma(ordinal(user_count))),
user=user,
)
if user_count == 5:
email = emails['new_api_user']
send_mail(
email['subject'],
email['body'] % user.first_name or 'there',
email['from'],
[user.email],
)
class LoggingMixin(object):
"""Log requests to Redis
This draws inspiration from the code that can be found at:
https://github.com/aschn/drf-tracking/blob/master/rest_framework_tracking/mixins.py
The big distinctions, however, are that this code uses Redis for greater
speed, and that it logs significantly less information.
We want to know:
- How many queries in last X days, total?
- How many queries ever, total?
- How many queries total made by user X?
- How many queries per day made by user X?
"""
milestones = get_milestone_range("SM", "XXXL")
def initial(self, request, *args, **kwargs):
super(LoggingMixin, self).initial(request, *args, **kwargs)
# For logging the timing in self.finalize_response
self.requested_at = now()
def finalize_response(self, request, response, *args, **kwargs):
response = super(LoggingMixin,
self).finalize_response(request, response, *args,
**kwargs)
if not response.exception:
# Don't log things like 401, 403, etc.,
# noinspection PyBroadException
try:
results = self._log_request(request)
self._handle_events(results, request.user)
except Exception as e:
logger.exception("Unable to log API response timing info: %s",
e.message)
return response
def _get_response_ms(self):
"""
Get the duration of the request response cycle in milliseconds.
In case of negative duration 0 is returned.
"""
response_timedelta = now() - self.requested_at
response_ms = int(response_timedelta.total_seconds() * 1000)
return max(response_ms, 0)
def _log_request(self, request):
d = date.today().isoformat()
user = request.user
endpoint = resolve(request.path_info).url_name
response_ms = self._get_response_ms()
r = make_redis_interface("STATS")
pipe = r.pipeline()
# Global and daily tallies for all URLs.
pipe.incr("api:v3.count")
pipe.incr("api:v3.d:%s.count" % d)
pipe.incr("api:v3.timing", response_ms)
pipe.incr("api:v3.d:%s.timing" % d, response_ms)
# Use a sorted set to store the user stats, with the score representing
# the number of queries the user made total or on a given day.
user_pk = user.pk or "AnonymousUser"
pipe.zincrby("api:v3.user.counts", 1, user_pk)
pipe.zincrby("api:v3.user.d:%s.counts" % d, 1, user_pk)
# Use a sorted set to store all the endpoints with score representing
# the number of queries the endpoint received total or on a given day.
pipe.zincrby("api:v3.endpoint.counts", 1, endpoint)
pipe.zincrby("api:v3.endpoint.d:%s.counts" % d, 1, endpoint)
# We create a per-day key in redis for timings. Inside the key we have
# members for every endpoint, with score of the total time. So to get
# the average for an endpoint you need to get the number of requests
# and the total time for the endpoint and divide.
timing_key = "api:v3.endpoint.d:%s.timings" % d
pipe.zincrby(timing_key, response_ms, endpoint)
results = pipe.execute()
return results
def _handle_events(self, results, user):
total_count = results[0]
user_count = results[4]
if total_count in MILESTONES_FLAT:
Event.objects.create(
description="API has logged %s total requests." % total_count)
if user.is_authenticated:
if user_count in self.milestones:
Event.objects.create(
description="User '%s' has placed their %s API request." %
(user.username, intcomma(ordinal(user_count))),
user=user,
)
if user_count == SEND_API_WELCOME_EMAIL_COUNT:
email = emails["new_api_user"]
send_mail(
email["subject"],
email["body"] % user.first_name or "there",
email["from"],
[user.email],
)
def test_milestone_ranges(self):
numbers = get_milestone_range('XS', 'SM')
self.assertEqual(numbers[0], 1e1)
self.assertEqual(numbers[-1], 5e4)
