Exemplo n.º 1
0
    def make_tables(self):
        start, end = promote.get_total_run(self.thing)

        if not start or not end:
            self.history = []
            return

        now = datetime.datetime.utcnow().replace(minute=0, second=0,
                                                 microsecond=0)
        end = min(end, now)
        cutoff = end - datetime.timedelta(days=31)
        start = max(start, cutoff)

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(fullname,
                                                                 start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(fullname,
                                                                   start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = _clickthrough_rate(u_imps, u_clicks)
            ctr = _clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = _clickthrough_rate(self.total_impressions,
                                                self.total_clicks)

        # XXX: _is_promo_preliminary correctly expects tz-aware datetimes
        # because it's also used with datetimes from promo code. this hack
        # relies on the fact that we're storing UTC w/o timezone info.
        # TODO: remove this when traffic is correctly using timezones.
        end_aware = end.replace(tzinfo=g.tz)
        self.is_preliminary = _is_promo_preliminary(end_aware)

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history
Exemplo n.º 2
0
    def make_tables(self):
        start, end = promote.get_total_run(self.thing)

        if not start or not end:
            self.history = []
            return

        cutoff = end - datetime.timedelta(days=31)
        start = max(start, cutoff)

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(fullname,
                                                                 start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(fullname,
                                                                   start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = _clickthrough_rate(u_imps, u_clicks)
            ctr = _clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = _clickthrough_rate(self.total_impressions,
                                                self.total_clicks)

        # XXX: _is_promo_preliminary correctly expects tz-aware datetimes
        # because it's also used with datetimes from promo code. this hack
        # relies on the fact that we're storing UTC w/o timezone info.
        # TODO: remove this when traffic is correctly using timezones.
        end_aware = end.replace(tzinfo=g.tz)
        self.is_preliminary = _is_promo_preliminary(end_aware)

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history
Exemplo n.º 3
0
    def get_tables(self):
        start, end = promote.get_total_run(self.thing)

        if not start or not end:
            self.history = []
            return

        cutoff = end - datetime.timedelta(days=31)
        start = max(start, cutoff)

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(
            fullname, start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(
            fullname, start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = self.calculate_clickthrough_rate(u_imps, u_clicks)
            ctr = self.calculate_clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = (
                (float(self.total_clicks) / self.total_impressions) * 100.)

        # the results are preliminary until 1 day after the promotion ends
        now = datetime.datetime.utcnow()
        self.is_preliminary = end + datetime.timedelta(days=1) > now

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history
Exemplo n.º 4
0
    def get_tables(self):
        start, end = promote.get_total_run(self.thing)

        if not start or not end:
            self.history = []
            return

        cutoff = end - datetime.timedelta(days=31)
        start = max(start, cutoff)

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(fullname,
                                                                 start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(fullname,
                                                                   start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = self.calculate_clickthrough_rate(u_imps, u_clicks)
            ctr = self.calculate_clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = ((float(self.total_clicks) /
                               self.total_impressions) * 100.)

        # the results are preliminary until 1 day after the promotion ends
        now = datetime.datetime.utcnow()
        self.is_preliminary = end + datetime.timedelta(days=1) > now

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history
Exemplo n.º 5
0
    def make_tables(self):
        now = datetime.datetime.utcnow().replace(minute=0, second=0,
                                                 microsecond=0)

        promo_start, promo_end = promote.get_total_run(self.thing)
        promo_end = min(now, promo_end)

        if not promo_start or not promo_end:
            self.history = []
            return

        if self.period:
            start = self.after
            end = self.before

            if not start and not end:
                end = promo_end
                start = end - self.period

            elif not end:
                end = start + self.period

            elif not start:
                start = end - self.period

            if start > promo_start:
                p = request.get.copy()
                p.update({'after':None, 'before':start.strftime('%Y%m%d%H')})
                self.prev = '%s?%s' % (request.path, urllib.urlencode(p))
            else:
                start = promo_start

            if end < promo_end:
                p = request.get.copy()
                p.update({'after':end.strftime('%Y%m%d%H'), 'before':None})
                self.next = '%s?%s' % (request.path, urllib.urlencode(p))
            else:
                end = promo_end
        else:
            start, end = promo_start, promo_end

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(fullname,
                                                                 start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(fullname,
                                                                   start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = _clickthrough_rate(u_imps, u_clicks)
            ctr = _clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = _clickthrough_rate(self.total_impressions,
                                                self.total_clicks)

        # XXX: _is_promo_preliminary correctly expects tz-aware datetimes
        # because it's also used with datetimes from promo code. this hack
        # relies on the fact that we're storing UTC w/o timezone info.
        # TODO: remove this when traffic is correctly using timezones.
        end_aware = end.replace(tzinfo=g.tz)
        self.is_preliminary = _is_promo_preliminary(end_aware)

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history
Exemplo n.º 6
0
    def make_tables(self):
        now = datetime.datetime.utcnow().replace(minute=0, second=0,
                                                 microsecond=0)

        promo_start, promo_end = promote.get_total_run(self.thing)
        promo_end = min(now, promo_end)

        if not promo_start or not promo_end:
            self.history = []
            return

        if self.period:
            start = self.after
            end = self.before

            if not start and not end:
                end = promo_end
                start = end - self.period

            elif not end:
                end = start + self.period

            elif not start:
                start = end - self.period

            if start > promo_start:
                p = request.get.copy()
                p.update({'after':None, 'before':start.strftime('%Y%m%d%H')})
                self.prev = '%s?%s' % (request.path, urllib.urlencode(p))
            else:
                start = promo_start

            if end < promo_end:
                p = request.get.copy()
                p.update({'after':end.strftime('%Y%m%d%H'), 'before':None})
                self.next = '%s?%s' % (request.path, urllib.urlencode(p))
            else:
                end = promo_end
        else:
            start, end = promo_start, promo_end

        fullname = self.thing._fullname
        imps = traffic.AdImpressionsByCodename.promotion_history(fullname,
                                                                 start, end)
        clicks = traffic.ClickthroughsByCodename.promotion_history(fullname,
                                                                   start, end)

        # promotion might have no clicks, zip_timeseries needs valid columns
        if imps and not clicks:
            clicks = [(imps[0][0], (0, 0))]

        history = traffic.zip_timeseries(imps, clicks, order="ascending")
        computed_history = []
        self.total_impressions, self.total_clicks = 0, 0
        for date, data in history:
            u_imps, imps, u_clicks, clicks = data

            u_ctr = _clickthrough_rate(u_imps, u_clicks)
            ctr = _clickthrough_rate(imps, clicks)

            self.total_impressions += imps
            self.total_clicks += clicks
            computed_history.append((date, data + (u_ctr, ctr)))

        self.history = computed_history

        if self.total_impressions > 0:
            self.total_ctr = _clickthrough_rate(self.total_impressions,
                                                self.total_clicks)

        # XXX: _is_promo_preliminary correctly expects tz-aware datetimes
        # because it's also used with datetimes from promo code. this hack
        # relies on the fact that we're storing UTC w/o timezone info.
        # TODO: remove this when traffic is correctly using timezones.
        end_aware = end.replace(tzinfo=g.tz)
        self.is_preliminary = _is_promo_preliminary(end_aware)

        # we should only graph a sane number of data points (not everything)
        self.max_points = traffic.points_for_interval("hour")

        return computed_history