Waterfall reports for subscriber activation

cloud/endagaweb/stats_app/stats_client.py

@@ -369,3 +369,149 @@ def timeseries(self, key=None, **kwargs):
         if 'aggregation' not in kwargs:
             kwargs['aggregation'] = 'average_value'
         return self.aggregate_timeseries(key, **kwargs)
+
+
+class WaterfallStatsClient(StatsClientBase):
+    """ waterfall reports data """
+
+    def __init__(self, *args, **kwargs):
+        super(WaterfallStatsClient, self).__init__(*args, **kwargs)
+
+    def timeseries(self, kind=None, **kwargs):
+        # Get report data in timeseries format
+        start_time_epoch = kwargs.pop('start_time_epoch', 0)
+        end_time_epoch = kwargs.pop('end_time_epoch', -1)
+
+        start = datetime.fromtimestamp(start_time_epoch, pytz.utc)
+        if end_time_epoch != -1:
+            end = datetime.fromtimestamp(end_time_epoch, pytz.utc)
+        else:
+            end = datetime.fromtimestamp(time.time(), pytz.utc)
+
+        response = {'header': [{'label': "Months", 'name': 'month',
+                                'frozen': True},
+                               {'label': "Subscriber Activation",
+                                'name': 'activation', 'frozen': True}],
+                    'data': []};
+
+        months = rrule(MONTHLY, dtstart=start, until=end)
+        for mnth in months:
+            key = mnth.strftime("%b") + "-" + mnth.strftime("%Y")
+            response['header'].append({'label': key, 'name': key})
+
+            # Get last/first date of month from selected month
+            next_month = mnth.replace(day=28) + timedelta(days=4)
+            stats_end_dt = next_month - timedelta(days=next_month.day)
+            stats_start_dt = mnth
+
+            kwargs['start_time_epoch'] = int(stats_start_dt.strftime("%s"))
+            kwargs['end_time_epoch'] = int(stats_end_dt.strftime("%s"))
+            kwargs['query'] = Q(subscriber__role='subscriber')
+            kind_key = 'Provisioned'
+            kwargs['report_view'] = 'value'
+            subscribers = self.aggregate_timeseries(kind_key, **kwargs)
+
+            month_row = {'month': key, 'activation': len(subscribers)}
+            for col_mnth in months:
+                col_key = col_mnth.strftime("%b") + "-" + col_mnth.strftime("%Y")
+                month_start_dt = col_mnth
+                # Get last date of month from selected month
+                next_month = col_mnth.replace(day=28) + timedelta(days=4)
+                month_end_dt = next_month - timedelta(days=next_month.day)
+
+                kwargs['start_time_epoch'] = int(month_start_dt.strftime("%s"))
+                kwargs['end_time_epoch'] = int(month_end_dt.strftime("%s"))
+                kwargs['query'] = Q(subscriber_id__in=subscribers)
+                if kind in ['loader', 'reload_rate']:
+                    kwargs['aggregation'] = 'loader'
+                    kwargs['report_view'] = 'value'
+                elif kind in ['reload_transaction', 'average_frequency']:
+                    kwargs['aggregation'] = 'count'
+                    kwargs['report_view'] = 'summary'
+                elif kind in ['reload_amount', 'average_load']:
+                    kwargs['aggregation'] = 'reload_transcation_sum'
+                    kwargs['report_view'] = 'summary'
+
+                result = self.aggregate_timeseries('transfer', **kwargs)
+                if isinstance(result, (list, tuple)):
+                    result = len(result)
+
+                if kind == 'reload_rate':
+                    try:
+                        pers = round(float(result) / len(subscribers), 2) * 100
+                    except:
+                        pers = 0
+                    result = str(pers) + " %"
+                elif kind in ['average_load', 'average_frequency']:
+                    kwargs['aggregation'] = 'loader'
+                    kwargs['report_view'] = 'value'
+                    loader = self.aggregate_timeseries('transfer', **kwargs)
+                    if isinstance(loader, (list, tuple)):
+                        loader = len(loader)
+                    try:
+                        result = round(float(result) / float(loader), 2)
+                    except:
+                        result = 0
+                month_row.update({col_key: result})
+            response['data'].append(month_row)
+        return response
+
+
+class NonLoaderStatsClient(StatsClientBase):
+    """ waterfall reports data """
+
+    def __init__(self, *args, **kwargs):
+        super(NonLoaderStatsClient, self).__init__(*args, **kwargs)
+
+    def timeseries(self, kind=None, **kwargs):
+        # Get report data in timeseries format
+        # Oldest subscriber provision date
+        start_time_epoch = 1406680050
+        last_month = datetime.fromtimestamp(time.time(),
+                                            pytz.utc) - timedelta(days=30)
+        end_epoch = last_month.replace(day=calendar.monthrange(
+            last_month.year, last_month.month)[1])
+        start_epoch = end_epoch - timedelta(6 * 365 / 12)
+
+        response = {'header': [{'label': "Months", 'name': 'month',
+                                'frozen': True},
+                               # {'label': "Activation", 'name': 'activation',
+                               # 'frozen': True},
+                               {'label': "Non Loader", 'name': 'nonloader',
+                                'frozen': True}],
+                    'data': []};
+
+        months = list(rrule(MONTHLY, dtstart=start_epoch, until=end_epoch))
+        months.sort(reverse=True)
+        kwargs2 = kwargs
+
+        counter = 1
+
+        for mnth in months:
+            key = mnth.strftime("%b") + "-" + mnth.strftime("%Y")
+
+            # Get last/first date of month from selected month
+            next_month = mnth.replace(day=28) + timedelta(days=4)
+            stats_end_dt = next_month - timedelta(days=next_month.day)
+            stats_start_dt = mnth.replace(day=1)
+
+            kwargs[
+                'start_time_epoch'] = start_time_epoch  # int(stats_start_dt.strftime("%s"))
+            kwargs['end_time_epoch'] = int(stats_end_dt.strftime("%s"))
+            kwargs['query'] = Q(subscriber__role='retailer')
+            kwargs['report_view'] = 'value'
+            subscribers = self.aggregate_timeseries('Provisioned', **kwargs)
+
+            kwargs2['start_time_epoch'] = int(stats_start_dt.strftime("%s"))
+            kwargs2['end_time_epoch'] = int(end_epoch.strftime("%s"))
+            kwargs2['query'] = Q(subscriber__role='retailer')
+            kwargs2['aggregation'] = 'count'
+            kwargs2['report_view'] = 'summary'
+
+            result = self.aggregate_timeseries('transfer', **kwargs2)
+            month_row = {'month': "%d months" % (counter),
+                         # 'activation': len(subscribers),
+                         'nonloader': result - len(subscribers)}
+            response['data'].append(month_row)
+            counter += 1
+        return response