def _comments(self, pivot_date):
pivot_date_min = datetime.combine(pivot_date,
time(0, 0, 0, 0, tzinfo=utc))
pivot_date_max = datetime.combine(pivot_date,
time(23, 59, 59, 999999, tzinfo=utc))
num_comments = Comments.objects.filter(
creation_date__range=(pivot_date_min, pivot_date_max)).count()
# Store data points
Metric.insert_metric(Metric.KPI_TOTAL_COMMENTS,
pivot_date,
num_comments,
segment=Metric.SEG_ALL)
return num_comments
def handle(self, *app_names, **options):
"""
Handle gathering the statistics
"""
verbosity = 1
if 'verbosity' in options:
verbosity = int(options['verbosity'])
# cache the user/member totals
self.users = self.get_users()
self.members = self.get_members()
# create a metric from the totals
metric = Metric()
metric.users = len(self.users)
metric.members = len(self.members)
metric.visits = len(self.get_visits())
metric.disk_usage = self.get_site_size()
if verbosity >= 2:
print 'metric.users', metric.users
print 'metric.members', metric.members
print 'metric.visits', metric.visits
print 'metric.disk_usage', metric.disk_usage
metric.save()
def index(request):
metrics = []
for MC in Metric.__subclasses__():
metrics.extend(MC.objects.all())
data = []
for metric in metrics:
latest = metric.data.latest()
data.append({'metric': metric, 'latest': latest})
return render(request, 'index.html', {'data': data})
def metrics(request):
key = get_agent_key(request)
host = Host.objects.get(agent_key=key)
host.save() # update last_updated
if not host.enabled:
return HttpResponse(status=403)
metrics = json.loads(request.body)
for metric in metrics:
# add counters
for counter in metric.get('counters'):
m = Metric()
m.metric_type = metric.get('type')
m.source = metric.get('container_id')
m.counter = counter.get('name')
m.value = counter.get('value')
m.unit = counter.get('unit')
m.save()
return HttpResponse()
def metrics(request):
key = get_agent_key(request)
host = Host.objects.get(agent_key=key)
host.save() # update last_updated
if not host.enabled:
return HttpResponse(status=403)
metrics = json.loads(request.body)
for metric in metrics:
# add counters
for counter in metric.get('counters'):
m = Metric()
m.metric_type = metric.get('type')
m.source = metric.get('container_id')
m.counter = counter.get('name')
m.value = counter.get('value')
m.unit = counter.get('unit')
m.save()
return HttpResponse()
def handle(self, *args, **options):
num_days = int(options.get('days', 7))
if options['custom_date']:
end_date = datetime.strptime(options['custom_date'], '%Y-%m-%d')
else:
end_date = now() - timedelta(days=1)
begin_date = end_date - timedelta(days=num_days)
begin_date_min = datetime.combine(begin_date, time(0, 0, 0, 0, tzinfo=utc))
end_date_max = datetime.combine(end_date, time(23, 59, 59, 999999, tzinfo=utc))
users = Chefs.objects.values('type')\
.filter(last_signin_date__range=(begin_date_min, end_date_max))\
.annotate(Count('type'))
# .exclude(creation_date=F(last_signin_date))
cnt_pro = 0
cnt_foodie = 0
for row in users:
if row['type'] == Chefs.TYPE_PRO:
cnt_pro += row['type__count']
else:
cnt_foodie += row['type__count']
# Store data points
if num_days == 7:
metric_code = Metric.KPI_SUPERACTIVE_USERS
elif num_days == 30:
metric_code = Metric.KPI_ACTIVE_USERS
elif num_days == 60:
metric_code = Metric.KPI_SLEEPING_USERS
else:
metric_code = Metric.KPI_DEAD_USERS
Metric.insert_metric(metric_code, end_date, cnt_foodie, segment=Metric.SEG_FOODIES)
Metric.insert_metric(metric_code, end_date, cnt_pro, segment=Metric.SEG_CHEFS)
Metric.insert_metric(metric_code, end_date, cnt_pro + cnt_foodie, segment=Metric.SEG_ALL)
self.stdout.write("%s user(s) registered" % (cnt_pro + cnt_foodie))
def handle_noargs(self, **options):
for MC in Metric.__subclasses__():
for metric in MC.objects.all():
metric.data.create(count=metric.fetch())
from django.contrib import admin
from metrics.models import Data, Metric
admin.site.register(Data)
for MC in Metric.__subclasses__():
admin.site.register(MC)
def handle(self, *args, **options):
if options['custom_date']:
pivot_date = datetime.strptime(options['custom_date'], '%Y-%m-%d')
else:
pivot_date = now() - timedelta(days=1)
pivot_date_min = datetime.combine(pivot_date,
time(0, 0, 0, 0, tzinfo=utc))
pivot_date_max = datetime.combine(pivot_date,
time(23, 59, 59, 999999, tzinfo=utc))
cnt_foodie = Recipes.objects.filter(
draft=0,
private=0,
creation_date__range=(pivot_date_min, pivot_date_max),
chef__type=Chefs.TYPE_FOODIE).count()
cnt_pro = Recipes.objects.filter(draft=0,
private=0,
creation_date__range=(pivot_date_min,
pivot_date_max),
chef__type=Chefs.TYPE_PRO).count()
# Store data points
Metric.insert_metric(Metric.KPI_TOTAL_RECIPES,
pivot_date,
cnt_foodie,
segment=Metric.SEG_FOODIES)
Metric.insert_metric(Metric.KPI_TOTAL_RECIPES,
pivot_date,
cnt_pro,
segment=Metric.SEG_CHEFS)
# Count recipes with more than 3 photos
cnt_foodie_plus_3 = Recipes.objects.filter(draft=0, private=0,
creation_date__range=(pivot_date_min, pivot_date_max),
chef__type=Chefs.TYPE_FOODIE)\
.annotate(photos_count=Count('photos'))\
.filter(photos_count__gt=3).count()
cnt_pro_plus_3 = Recipes.objects.filter(draft=0, private=0,
creation_date__range=(pivot_date_min, pivot_date_max),
chef__type=Chefs.TYPE_PRO)\
.annotate(photos_count=Count('photos'))\
.filter(photos_count__gt=3).count()
# Store data points
Metric.insert_metric(Metric.KPI_TOTAL_RECIPES_3_PHOTOS,
pivot_date,
cnt_foodie_plus_3,
segment=Metric.SEG_FOODIES)
Metric.insert_metric(Metric.KPI_TOTAL_RECIPES_3_PHOTOS,
pivot_date,
cnt_pro_plus_3,
segment=Metric.SEG_CHEFS)
# Send data to Dashboard
GeckoBoard.push_recipes_created(cnt_foodie_plus_3 + cnt_pro_plus_3,
cnt_pro_plus_3, cnt_foodie_plus_3)
self.stdout.write("%s Total foodies recipes created" % cnt_foodie)
self.stdout.write("%s Total chefs recipes created" % cnt_pro)
self.stdout.write("%s foodies recipes with more than 3 photos" %
cnt_foodie_plus_3)
self.stdout.write("%s chefs recipes with more than 3 photos" %
cnt_pro_plus_3)
def create_metrics(apps, schema_editor):
"""Create one metric"""
metric = Metric()
metric.name = 'confidence'
metric.description = 'Tracks model confidence'
metric.save()
metric = Metric()
metric.name = 'Image size'
metric.description = 'Records input image size'
metric.save()
metric = Metric()
metric.name = 'Pixel intensity'
metric.description = 'Records pixel average intensity of your images'
metric.save()
def handle(self, *args, **options):
if options['custom_date']:
pivot_date = datetime.strptime(options['custom_date'], '%Y-%m-%d')
else:
pivot_date = now() - timedelta(days=1)
pivot_date_min = datetime.combine(pivot_date,
time(0, 0, 0, 0, tzinfo=utc))
pivot_date_max = datetime.combine(pivot_date,
time(23, 59, 59, 999999, tzinfo=utc))
registered_users = Chefs.objects.values('type')\
.filter(creation_date__range=(pivot_date_min, pivot_date_max))\
.annotate(Count('type'))
cnt_pro = 0
cnt_foodie = 0
for row in registered_users:
if row['type'] == Chefs.TYPE_PRO:
cnt_pro += row['type__count']
else:
cnt_foodie += row['type__count']
# Store data points
Metric.insert_metric(Metric.KPI_REGISTERED_USERS,
pivot_date,
cnt_foodie,
segment=Metric.SEG_FOODIES)
Metric.insert_metric(Metric.KPI_REGISTERED_USERS,
pivot_date,
cnt_pro,
segment=Metric.SEG_CHEFS)
Metric.insert_metric(Metric.KPI_REGISTERED_USERS,
pivot_date,
cnt_pro + cnt_foodie,
segment=Metric.SEG_ALL)
# Count total foodies
total_foodies = Chefs.objects.filter(is_active=True,
active=True,
type=Chefs.TYPE_FOODIE).count()
Metric.insert_metric(Metric.KPI_TOTAL_USERS,
pivot_date,
total_foodies,
segment=Metric.SEG_FOODIES)
total_chefs = Chefs.objects.filter(is_active=True,
active=True,
type=Chefs.TYPE_PRO).count()
Metric.insert_metric(Metric.KPI_TOTAL_USERS,
pivot_date,
total_chefs,
segment=Metric.SEG_CHEFS)
# Push to dashboard
GeckoBoard.push_weekly_metric(Metric.KPI_REGISTERED_USERS)
self.stdout.write("%s user(s) registered" % (cnt_pro + cnt_foodie))
self.stdout.write("Total foodies %s registered" % total_foodies)
self.stdout.write("Total chefs %s registered" % total_chefs)
from django.contrib import admin
from metrics.models import Data, Metric
admin.site.register(Data)
for MC in Metric.__subclasses__():
admin.site.register(MC)
