def getSpecificCampaignNew(campaign):
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
campaign = campaign.replace('^&^', '#')
campaign = campaign.replace('^^^', '?')
data = queryToData(cur2,queries.list_one_campaign.format(campaign),need_json=0)
if data[0]['mobile_ids'] is not None and data[0]['mobile_ids'] != '0':
c_id = ",".join(['"'+i+'"' for i in data[0]['mobile_ids'].split(',') if i != 0])
else:
c_id = "'999'"
if int(data[0]['is_sms']) == 0:
total_su = queryToData(cur2,queries.signups_total.format(c_id, data[0]['nid'], '2000-01-01', '3000-01-01'), index=0, keyname='total_signups', need_json=0)
total_web_su = queryToData(cur2,queries.signups_web.format(data[0]['nid'], '2000-01-01', '3000-01-01'), index=0, keyname='web_su', need_json=0)
total_nm = queryToData(cur2,queries.new_members_total.format(c_id, data[0]['nid'], '2000-01-01', '3000-01-01'), index=0, keyname='new_members_total', need_json=0)
total_rb = queryToData(cur2,queries.report_back_total_web.format(data[0]['nid'], '10000', '2000-01-01', '3000-01-01'), index=0, keyname='rb', need_json=0)
total_impact = queryToData(cur2,queries.impact_total.format(data[0]['nid'], '10000', '2000-01-01', '3000-01-01'), index=0, keyname='impact', need_json=0)
total_traffic = queryToData(cur2,queries.traffic_total.format(data[0]['nid'], '2000-01-01', '3000-01-01'), index=0, keyname='traffic', need_json=0)
overall = OrderedDict([('Sign Ups',total_su), ('New Members',total_nm), ('Reportbacks',total_rb), ('Impact',total_impact), ('Traffic',total_traffic), ('Conversion Rate',round(float(total_web_su)/float(total_traffic) * 100, 2))])
overall = json.dumps(overall)
su = queryToData(cur2,queries.new_sign_ups_new.format(c_id, data[0]['nid'], '2000-01-01', '3000-01-01'))
nm = queryToData(cur2,queries.new_members_new.format(c_id, data[0]['nid'], '2000-01-01', '3000-01-01'))
rb = queryToData(cur2,queries.reportback_web_daily.format(data[0]['nid'], '10000', '2000-01-01', '3000-01-01'))
impact = queryToData(cur2,queries.impact_daily.format(data[0]['nid'], '10000', '2000-01-01', '3000-01-01'))
srcs = queryToData(cur2,queries.sources_new.format(data[0]['nid'], '2000-01-01', '3000-01-01'))
traffic = queryToData(cur2,queries.traffic_daily.format(data[0]['nid'], '2000-01-01', '3000-01-01'))
if int(data[0]['is_sms']) == 1:
total_su = queryToData(cur2,queries.new_sign_ups_new_mobile_total.format(c_id, '2000-01-01', '3000-01-01'), index=0, keyname='mobile_signup_total', need_json=0)
total_nm = queryToData(cur2,queries.new_members_new_mobile_total.format(c_id, '2000-01-01', '3000-01-01'), index=0, keyname='mobile_new_members_total', need_json=0)
total_alpha = queryToData(cur2,queries.new_sign_ups_new_alphas.format(c_id, '2000-01-01', '3000-01-01'), index=0, keyname='alphas', need_json=0)
total_traffic = queryToData(cur2,queries.traffic_total.format(data[0]['nid'], '2000-01-01', '3000-01-01'), index=0, keyname='traffic', need_json=0)
overall = OrderedDict([('Sign Ups',total_su), ('New Members',total_nm), ('Reportbacks',total_alpha), ('Impact',total_alpha), ('Traffic',total_traffic), ('Conversion Rate',round(float(total_alpha)/float(total_traffic) * 100, 2))])
overall = json.dumps(overall)
su = queryToData(cur2,queries.new_sign_ups_new_mobile.format(c_id, '2000-01-01', '3000-01-01'))
nm = queryToData(cur2,queries.new_members_new_mobile.format(c_id, '2000-01-01', '3000-01-01'))
rb = queryToData(cur2,queries.reportback_sms_daily.format(c_id, '2000-01-01', '3000-01-01'))
impact = 0
srcs = queryToData(cur2,queries.sources_new.format(data[0]['nid'], '2000-01-01', '3000-01-01'))
traffic = queryToData(cur2,queries.traffic_daily.format(data[0]['nid'], '2000-01-01', '3000-01-01'))
cur2.close()
db2.close()
return render_template('campaign-new.html', is_sms=data[0]['is_sms'], campaign=campaign, su=su, nm=nm, rb=rb, impact=impact, srcs=srcs, overall=overall, traffic=traffic)
def causeStaffPicks(cause):
title = cause.capitalize()
causes_list = cause.split("+")
if request.args.get('staff') is None:
staff = "y"
else:
staff = request.args.get('staff')
quoted_causes = ['"'+str(cause)+'"' for cause in causes_list]
formatted_causes = ','.join(quoted_causes)
if cause != 'all':
q = 'select concat(upper(substring(replace(campaign,"_"," "),1,1)),substring(replace(campaign,"_"," "),2)) as campaign, sign_ups, new_members, report_backs from overall.overall where staff_pick = "%s" and cause in (%s) and date_add(end_date, interval 7 day) >= curdate() order by sign_ups desc' % (staff,formatted_causes)
else:
q = 'select concat(upper(substring(replace(campaign,"_"," "),1,1)),substring(replace(campaign,"_"," "),2)) as campaign, sign_ups, new_members, report_backs from overall.overall where staff_pick = "%s" and date_add(end_date, interval 7 day) >= curdate() order by sign_ups desc' % (staff)
cur = openDB()
cur.execute(q)
data = cur.fetchall()
cur.close()
j = json.dumps(data)
if len(data) > 0:
return render_template('cause-campaigns.html', title=title,causes=cause, j=j)
else:
return render_template('cause-campaigns-nodata.html', title=title,causes=cause)
def getCausesdata():
cur = openDB()
#all_casues needed for chart
q = """
select 'Sex+Relationships' as cause, group_concat(distinct cause) as all_causes, sum(sign_ups) as sign_ups, sum(new_members) as new_members, sum(report_backs) as report_backs, sum(all_traffic) as traffic, round(avg(avg_gate_conversion)*100,2) as conv, count(*) as campaigns from overall.overall where date_add(end_date, interval 14 day) >= curdate() and cause in ('Sex',"Relationships")
union all
select 'Homelessness+Poverty' as cause, group_concat(distinct cause) as all_causes, sum(sign_ups) as sign_ups, sum(new_members) as new_members, sum(report_backs) as report_backs, sum(all_traffic) as traffic, round(avg(avg_gate_conversion)*100,2) as conv, count(*) as campaigns from overall.overall where date_add(end_date, interval 14 day) >= curdate() and cause in ('Homelessness',"Poverty")
union all
select 'Bullying+Violence' as cause, group_concat(distinct cause) as all_causes, sum(sign_ups) as sign_ups, sum(new_members) as new_members, sum(report_backs) as report_backs, sum(all_traffic) as traffic, round(avg(avg_gate_conversion)*100,2) as conv, count(*) as campaigns from overall.overall where date_add(end_date, interval 14 day) >= curdate() and cause in ('Bullying',"Violence")
union all
select 'Mental Health+Physical Health' as cause, group_concat(distinct cause) as all_causes, sum(sign_ups) as sign_ups, sum(new_members) as new_members, sum(report_backs) as report_backs, sum(all_traffic) as traffic, round(avg(avg_gate_conversion)*100,2) as conv, count(*) as campaigns from overall.overall where date_add(end_date, interval 14 day) >= curdate() and cause in ('Mental Health',"Physical Health")
union all
select cause, group_concat(distinct cause) as all_causes, sum(sign_ups) as sign_ups, sum(new_members) as new_members, sum(report_backs) as report_backs, sum(all_traffic) as traffic, round(avg(avg_gate_conversion)*100,2) as conv, count(*) as campaigns from overall.overall where date_add(end_date, interval 14 day) >= curdate() and cause not in ('Bullying',"Violence",'Mental Health',"Physical Health",'Homelessness',"Poverty",'Sex',"Relationships") group by cause
"""
cur.execute(q)
data = cur.fetchall()
cur.close()
json.dumps(data)
return json.dumps(data)
def listCampaigns():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2,queries.list_all_campaigns, need_json=0)
data = [{'title':i['title'].decode('ascii', 'ignore')} for i in data]
data = json.dumps(data)
cur2.close()
db2.close()
return render_template('list-campaigns.html', data=data)
def listCampaigns():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2, queries.list_all_campaigns, need_json=0)
data = [{'title': i['title'].decode('ascii', 'ignore')} for i in data]
data = json.dumps(data)
cur2.close()
db2.close()
return render_template('list-campaigns.html', data=data)
def monthly():
cur = openDB()
cur.execute('select date_format(date, "%M %Y") as date, new_members_last_12_percent as new, engaged_members_last_12_percent as engaged, active_members_last_12_percent as active, verified_members_last_12_percent as verified from members.bod_2014 order by date_format(date, "%Y-%m-%d")' )
d = cur.fetchall()
cur.close()
data = json.dumps(d)
return render_template('monthly-stats.html', data=data )
def campaignDataEnpoint(nid):
try:
nid = int(nid)
q_metadata = queries.campaignDataEnpoint_basic_campaign_metadata % (nid)
db_obj = openDB()
db = db_obj[0]
cur = db_obj[1]
text = queryToData(cur,q_metadata)
cur.close()
db.close()
return text
except:
return json.dumps({'error':500})
def campaignDataEnpoint(nid):
try:
nid = int(nid)
q_metadata = queries.campaignDataEnpoint_basic_campaign_metadata % (
nid)
db_obj = openDB()
db = db_obj[0]
cur = db_obj[1]
text = queryToData(cur, q_metadata)
cur.close()
db.close()
return text
except:
return json.dumps({'error': 500})
def formatDemo(query, name_present):
cur2.execute(query)
out = cur2.fetchall()
#format json data for lists
master_list = {'header':out[0]['header'], 'item_list':list()}
for item in out:
counts = [int(num) for num in item['count'].split(",")]
total = sum(counts)
#create percent str
percents = [str(round((i/float(total))*100,2)) + '%' for i in counts]
metric = item['metric'].split(",")
inner_dict = dict(zip(metric,percents))
if name_present is True:
temp_dict = {item['name']:inner_dict}
else:
temp_dict = inner_dict
master_list['item_list'].append(temp_dict)
return json.dumps(master_list)
def formatDemo(query, name_present):
cur2.execute(query)
out = cur2.fetchall()
#format json data for lists
master_list = {'header': out[0]['header'], 'item_list': list()}
for item in out:
counts = [int(num) for num in item['count'].split(",")]
total = sum(counts)
#create percent str
percents = [
str(round((i / float(total)) * 100, 2)) + '%' for i in counts
]
metric = item['metric'].split(",")
inner_dict = dict(zip(metric, percents))
if name_present is True:
temp_dict = {item['name']: inner_dict}
else:
temp_dict = inner_dict
master_list['item_list'].append(temp_dict)
return json.dumps(master_list)
def query(name,query): cur.execute(query) info = json.dumps(cur.fetchall()) data[name]=info
def dateRange():
#gets new start and end from ajax post and pulls queries with new parameters
start = request.form['start']
end = request.form['end']
campaign = request.form['campaign']
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2,queries.list_one_campaign.format(campaign),need_json=0)
if data[0]['mobile_ids'] is not None and data[0]['mobile_ids'] != '0':
c_id = ",".join(['"'+i+'"' for i in data[0]['mobile_ids'].split(',') if i != 0])
else:
c_id = "'999'"
if int(data[0]['is_sms']) == 0:
total_su = queryToData(cur2,queries.signups_total.format(c_id, data[0]['nid'], start, end), index=0, keyname='total_signups', need_json=0)
total_web_su = queryToData(cur2,queries.signups_web.format(data[0]['nid'], start, end), index=0, keyname='web_su', need_json=0)
total_nm = queryToData(cur2,queries.new_members_total.format(c_id, data[0]['nid'], start, end), index=0, keyname='new_members_total', need_json=0)
total_rb = queryToData(cur2,queries.report_back_total_web.format(data[0]['nid'], '10000', start, end), index=0, keyname='rb', need_json=0)
total_impact = queryToData(cur2,queries.impact_total.format(data[0]['nid'], '10000', start, end), index=0, keyname='impact', need_json=0)
total_traffic = queryToData(cur2,queries.traffic_total.format(data[0]['nid'], start, end), index=0, keyname='traffic', need_json=0)
try:
conv_rate = round(float(total_web_su)/float(total_traffic) * 100, 2)
except:
conv_rate = 0.0
overall = OrderedDict([('Sign Ups',total_su), ('New Members',total_nm), ('Reportbacks',total_rb), ('Impact',total_impact), ('Traffic',total_traffic), ('Conversion Rate',conv_rate)])
overall = json.dumps(overall)
su = queryToData(cur2,queries.new_sign_ups_new.format(c_id, data[0]['nid'], start, end))
nm = queryToData(cur2,queries.new_members_new.format(c_id, data[0]['nid'], start, end))
rb = queryToData(cur2,queries.reportback_web_daily.format(data[0]['nid'], '10000', start, end))
impact = queryToData(cur2,queries.impact_daily.format(data[0]['nid'], '10000', start, end))
srcs = queryToData(cur2,queries.sources_new.format(data[0]['nid'], start, end))
traffic = queryToData(cur2,queries.traffic_daily.format(data[0]['nid'], start, end))
if int(data[0]['is_sms']) == 1:
total_su = queryToData(cur2,queries.new_sign_ups_new_mobile_total.format(c_id, start, end), index=0, keyname='mobile_signup_total', need_json=0)
total_nm = queryToData(cur2,queries.new_members_new_mobile_total.format(c_id, start, end), index=0, keyname='mobile_new_members_total', need_json=0)
total_alpha = queryToData(cur2,queries.new_sign_ups_new_alphas.format(c_id, start, end), index=0, keyname='alphas', need_json=0)
total_traffic = queryToData(cur2,queries.traffic_total.format(data[0]['nid'], start, end), index=0, keyname='traffic', need_json=0)
try:
conv_rate = round(float(total_alpha)/float(total_traffic) * 100, 2)
except:
conv_rate = 0.0
overall = OrderedDict([('Sign Ups',total_su), ('New Members',total_nm), ('Reportbacks',total_alpha), ('Impact',total_alpha), ('Traffic',total_traffic), ('Conversion Rate',conv_rate)])
overall = json.dumps(overall)
su = queryToData(cur2,queries.new_sign_ups_new_mobile.format(c_id, start, end))
nm = queryToData(cur2,queries.new_members_new_mobile.format(c_id, start, end))
rb = queryToData(cur2,queries.reportback_sms_daily.format(c_id, start, end))
impact = 0
srcs = queryToData(cur2,queries.sources_new.format(data[0]['nid'], start, end))
traffic = queryToData(cur2,queries.traffic_daily.format(data[0]['nid'], start, end))
cur2.close()
db2.close()
return jsonify(is_sms=data[0]['is_sms'], campaign=campaign, su=su, nm=nm, rb=rb, impact=impact, srcs=srcs, overall=overall, traffic=traffic)
def dateRange():
#gets new start and end from ajax post and pulls queries with new parameters
start = request.form['start']
end = request.form['end']
campaign = request.form['campaign']
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2,
queries.list_one_campaign.format(campaign),
need_json=0)
if data[0]['mobile_ids'] is not None and data[0]['mobile_ids'] != '0':
c_id = ",".join([
'"' + i + '"' for i in data[0]['mobile_ids'].split(',') if i != 0
])
else:
c_id = "'999'"
if int(data[0]['is_sms']) == 0:
total_su = queryToData(cur2,
queries.signups_total.format(
c_id, data[0]['nid'], start, end),
index=0,
keyname='total_signups',
need_json=0)
total_web_su = queryToData(cur2,
queries.signups_web.format(
data[0]['nid'], start, end),
index=0,
keyname='web_su',
need_json=0)
total_nm = queryToData(cur2,
queries.new_members_total.format(
c_id, data[0]['nid'], start, end),
index=0,
keyname='new_members_total',
need_json=0)
total_rb = queryToData(cur2,
queries.report_back_total_web.format(
data[0]['nid'], '10000', start, end),
index=0,
keyname='rb',
need_json=0)
total_impact = queryToData(cur2,
queries.impact_total.format(
data[0]['nid'], '10000', start, end),
index=0,
keyname='impact',
need_json=0)
total_traffic = queryToData(cur2,
queries.traffic_total.format(
data[0]['nid'], start, end),
index=0,
keyname='traffic',
need_json=0)
try:
conv_rate = round(
float(total_web_su) / float(total_traffic) * 100, 2)
except:
conv_rate = 0.0
overall = OrderedDict([('Sign Ups', total_su),
('New Members', total_nm),
('Reportbacks', total_rb),
('Impact', total_impact),
('Traffic', total_traffic),
('Conversion Rate', conv_rate)])
overall = json.dumps(overall)
su = queryToData(
cur2,
queries.new_sign_ups_new.format(c_id, data[0]['nid'], start, end))
nm = queryToData(
cur2,
queries.new_members_new.format(c_id, data[0]['nid'], start, end))
rb = queryToData(
cur2,
queries.reportback_web_daily.format(data[0]['nid'], '10000', start,
end))
impact = queryToData(
cur2,
queries.impact_daily.format(data[0]['nid'], '10000', start, end))
srcs = queryToData(
cur2, queries.sources_new.format(data[0]['nid'], start, end))
traffic = queryToData(
cur2, queries.traffic_daily.format(data[0]['nid'], start, end))
if int(data[0]['is_sms']) == 1:
total_su = queryToData(cur2,
queries.new_sign_ups_new_mobile_total.format(
c_id, start, end),
index=0,
keyname='mobile_signup_total',
need_json=0)
total_nm = queryToData(cur2,
queries.new_members_new_mobile_total.format(
c_id, start, end),
index=0,
keyname='mobile_new_members_total',
need_json=0)
total_alpha = queryToData(cur2,
queries.new_sign_ups_new_alphas.format(
c_id, start, end),
index=0,
keyname='alphas',
need_json=0)
total_traffic = queryToData(cur2,
queries.traffic_total.format(
data[0]['nid'], start, end),
index=0,
keyname='traffic',
need_json=0)
try:
conv_rate = round(
float(total_alpha) / float(total_traffic) * 100, 2)
except:
conv_rate = 0.0
overall = OrderedDict([('Sign Ups', total_su),
('New Members', total_nm),
('Reportbacks', total_alpha),
('Impact', total_alpha),
('Traffic', total_traffic),
('Conversion Rate', conv_rate)])
overall = json.dumps(overall)
su = queryToData(
cur2, queries.new_sign_ups_new_mobile.format(c_id, start, end))
nm = queryToData(
cur2, queries.new_members_new_mobile.format(c_id, start, end))
rb = queryToData(cur2,
queries.reportback_sms_daily.format(c_id, start, end))
impact = 0
srcs = queryToData(
cur2, queries.sources_new.format(data[0]['nid'], start, end))
traffic = queryToData(
cur2, queries.traffic_daily.format(data[0]['nid'], start, end))
cur2.close()
db2.close()
return jsonify(is_sms=data[0]['is_sms'],
campaign=campaign,
su=su,
nm=nm,
rb=rb,
impact=impact,
srcs=srcs,
overall=overall,
traffic=traffic)
def getSpecificCampaignNew(campaign):
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
campaign = campaign.replace('^&^', '#')
campaign = campaign.replace('^^^', '?')
data = queryToData(cur2,
queries.list_one_campaign.format(campaign),
need_json=0)
if data[0]['mobile_ids'] is not None and data[0]['mobile_ids'] != '0':
c_id = ",".join([
'"' + i + '"' for i in data[0]['mobile_ids'].split(',') if i != 0
])
else:
c_id = "'999'"
if int(data[0]['is_sms']) == 0:
total_su = queryToData(cur2,
queries.signups_total.format(
c_id, data[0]['nid'], '2000-01-01',
'3000-01-01'),
index=0,
keyname='total_signups',
need_json=0)
total_web_su = queryToData(cur2,
queries.signups_web.format(
data[0]['nid'], '2000-01-01',
'3000-01-01'),
index=0,
keyname='web_su',
need_json=0)
total_nm = queryToData(cur2,
queries.new_members_total.format(
c_id, data[0]['nid'], '2000-01-01',
'3000-01-01'),
index=0,
keyname='new_members_total',
need_json=0)
total_rb = queryToData(cur2,
queries.report_back_total_web.format(
data[0]['nid'], '10000', '2000-01-01',
'3000-01-01'),
index=0,
keyname='rb',
need_json=0)
total_impact = queryToData(cur2,
queries.impact_total.format(
data[0]['nid'], '10000', '2000-01-01',
'3000-01-01'),
index=0,
keyname='impact',
need_json=0)
total_traffic = queryToData(cur2,
queries.traffic_total.format(
data[0]['nid'], '2000-01-01',
'3000-01-01'),
index=0,
keyname='traffic',
need_json=0)
overall = OrderedDict([
('Sign Ups', total_su), ('New Members', total_nm),
('Reportbacks', total_rb), ('Impact', total_impact),
('Traffic', total_traffic),
('Conversion Rate',
round(float(total_web_su) / float(total_traffic) * 100, 2))
])
overall = json.dumps(overall)
su = queryToData(
cur2,
queries.new_sign_ups_new.format(c_id, data[0]['nid'], '2000-01-01',
'3000-01-01'))
nm = queryToData(
cur2,
queries.new_members_new.format(c_id, data[0]['nid'], '2000-01-01',
'3000-01-01'))
rb = queryToData(
cur2,
queries.reportback_web_daily.format(data[0]['nid'], '10000',
'2000-01-01', '3000-01-01'))
impact = queryToData(
cur2,
queries.impact_daily.format(data[0]['nid'], '10000', '2000-01-01',
'3000-01-01'))
srcs = queryToData(
cur2,
queries.sources_new.format(data[0]['nid'], '2000-01-01',
'3000-01-01'))
traffic = queryToData(
cur2,
queries.traffic_daily.format(data[0]['nid'], '2000-01-01',
'3000-01-01'))
if int(data[0]['is_sms']) == 1:
total_su = queryToData(cur2,
queries.new_sign_ups_new_mobile_total.format(
c_id, '2000-01-01', '3000-01-01'),
index=0,
keyname='mobile_signup_total',
need_json=0)
total_nm = queryToData(cur2,
queries.new_members_new_mobile_total.format(
c_id, '2000-01-01', '3000-01-01'),
index=0,
keyname='mobile_new_members_total',
need_json=0)
total_alpha = queryToData(cur2,
queries.new_sign_ups_new_alphas.format(
c_id, '2000-01-01', '3000-01-01'),
index=0,
keyname='alphas',
need_json=0)
total_traffic = queryToData(cur2,
queries.traffic_total.format(
data[0]['nid'], '2000-01-01',
'3000-01-01'),
index=0,
keyname='traffic',
need_json=0)
overall = OrderedDict([
('Sign Ups', total_su), ('New Members', total_nm),
('Reportbacks', total_alpha), ('Impact', total_alpha),
('Traffic', total_traffic),
('Conversion Rate',
round(float(total_alpha) / float(total_traffic) * 100, 2))
])
overall = json.dumps(overall)
su = queryToData(
cur2,
queries.new_sign_ups_new_mobile.format(c_id, '2000-01-01',
'3000-01-01'))
nm = queryToData(
cur2,
queries.new_members_new_mobile.format(c_id, '2000-01-01',
'3000-01-01'))
rb = queryToData(
cur2,
queries.reportback_sms_daily.format(c_id, '2000-01-01',
'3000-01-01'))
impact = 0
srcs = queryToData(
cur2,
queries.sources_new.format(data[0]['nid'], '2000-01-01',
'3000-01-01'))
traffic = queryToData(
cur2,
queries.traffic_daily.format(data[0]['nid'], '2000-01-01',
'3000-01-01'))
cur2.close()
db2.close()
return render_template('campaign-new.html',
is_sms=data[0]['is_sms'],
campaign=campaign,
su=su,
nm=nm,
rb=rb,
impact=impact,
srcs=srcs,
overall=overall,
traffic=traffic)