def kpis():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
q_active = queries.kpisActive
active = queryToData(cur2,q_active)
q_verified_all_s = queries.kpisVerifiedAll_S
verified_all_s = queryToData(cur2,q_verified_all_s)
q_verified_all_w = queries.kpisVerifiedAll_W
verified_all_w = queryToData(cur2,q_verified_all_w)
q_new = queries.kpisNew
new = queryToData(cur2,q_new)
q_text = queries.kpiText
text = queryToData(cur2,q_text)
cur2.close()
db2.close()
return render_template('kpi_page.html', active=active, verified_all_w=verified_all_w, verified_all_s=verified_all_s, new_m=new, q_text=text, user_role=g.user.role)
def home():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2, queries.home_total_members, 0, 'total')
data = int(json.loads(data))
formatted_data = formatThousandNumber(data)
data2_f = queryToData(cur2, queries.home_net_members_daily)
data3_f = queryToData(cur2, queries.home_gross_mobile_new_members)
data4_f = queryToData(cur2, queries.home_gross_mail_new_members)
data5_f = queryToData(cur2, queries.home_gross_mobile_optedout_members)
data6_f = queryToData(cur2, queries.home_gross_mail_optedout_members)
cur2.close()
db2.close()
return render_template('home.html',
formatted_data=formatted_data,
data2=data2_f,
data3=data3_f,
data4=data4_f,
data5=data5_f,
data6=data6_f)
def kpis():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
q_active = queries.kpisActive
active = queryToData(cur2, q_active)
q_verified_all_s = queries.kpisVerifiedAll_S
verified_all_s = queryToData(cur2, q_verified_all_s)
q_verified_all_w = queries.kpisVerifiedAll_W
verified_all_w = queryToData(cur2, q_verified_all_w)
q_new = queries.kpisNew
new = queryToData(cur2, q_new)
q_text = queries.kpiText
text = queryToData(cur2, q_text)
cur2.close()
db2.close()
return render_template('kpi_page.html',
active=active,
verified_all_w=verified_all_w,
verified_all_s=verified_all_s,
new_m=new,
q_text=text,
user_role=g.user.role)
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 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 campaignSearch(): db2_obj = openDB2() db2 = db2_obj[0] cur2 = db2_obj[1] search_str = request.form['search_str'] campaigns = queryToData(cur2,queries.search_campaigns.format(search_str)) cur2.close() db2.close() return jsonify(campaigns=campaigns)
def campaignSearch():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
search_str = request.form['search_str']
campaigns = queryToData(cur2, queries.search_campaigns.format(search_str))
cur2.close()
db2.close()
return jsonify(campaigns=campaigns)
def kpisubmit():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
#get rid of quotes aspostraphes when writing to mysql, and replace them later when called to the page
text = request.form['text'].replace("'","|").replace('"',"%^&")
q_insert = queries.kpiTextInsert % (dt.now(), text, request.form['box_id'])
cur2.execute(q_insert)
db2.commit()
cur2.close()
db2.close()
return q_insert
def kpisubmit():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
#get rid of quotes aspostraphes when writing to mysql, and replace them later when called to the page
text = request.form['text'].replace("'", "|").replace('"', "%^&")
q_insert = queries.kpiTextInsert % (dt.now(), text, request.form['box_id'])
cur2.execute(q_insert)
db2.commit()
cur2.close()
db2.close()
return q_insert
def demographicsPull():
#open db connect
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
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)
action_gender = formatDemo(queries.demographics_action_gender, True)
action_income = formatDemo(queries.demographics_action_income, True)
cause_gender = formatDemo(queries.demographics_cause_gender, True)
cause_income = formatDemo(queries.demographics_cause_income, True)
#to use this data, just uncomment!
#formatDemo(queries.demographics_mobile_age, False)
#formatDemo(queries.demographics_mobile_gender, False)
#formatDemo(queries.demographics_mobile_income, False)
#formatDemo(queries.demographics_mobile_race, False)
#formatDemo(queries.demographics_web_age, False)
#formatDemo(queries.demographics_web_gender, False)
#formatDemo(queries.demographics_web_race, False)
cur2.close()
db2.close()
return render_template('demographics.html',
action_gender=action_gender,
cause_gender=cause_gender,
action_income=action_income,
cause_income=cause_income)
def demographicsPull():
#open db connect
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
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)
action_gender = formatDemo(queries.demographics_action_gender, True)
action_income = formatDemo(queries.demographics_action_income, True)
cause_gender = formatDemo(queries.demographics_cause_gender, True)
cause_income = formatDemo(queries.demographics_cause_income, True)
#to use this data, just uncomment!
#formatDemo(queries.demographics_mobile_age, False)
#formatDemo(queries.demographics_mobile_gender, False)
#formatDemo(queries.demographics_mobile_income, False)
#formatDemo(queries.demographics_mobile_race, False)
#formatDemo(queries.demographics_web_age, False)
#formatDemo(queries.demographics_web_gender, False)
#formatDemo(queries.demographics_web_race, False)
cur2.close()
db2.close()
return render_template('demographics.html', action_gender=action_gender, cause_gender=cause_gender, action_income=action_income, cause_income=cause_income)
def home():
db2_obj = openDB2()
db2 = db2_obj[0]
cur2 = db2_obj[1]
data = queryToData(cur2,queries.home_total_members,0,'total')
data = int(json.loads(data))
formatted_data = formatThousandNumber(data)
data2_f = queryToData(cur2,queries.home_net_members_daily)
data3_f = queryToData(cur2,queries.home_gross_mobile_new_members)
data4_f = queryToData(cur2,queries.home_gross_mail_new_members)
data5_f = queryToData(cur2,queries.home_gross_mobile_optedout_members)
data6_f = queryToData(cur2,queries.home_gross_mail_optedout_members)
cur2.close()
db2.close()
return render_template('home.html',formatted_data=formatted_data, data2 = data2_f, data3 = data3_f, data4 = data4_f, data5 = data5_f, data6 = data6_f)
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)