def generate_summary(request):
try:
err_msg = ''
"""
PROCESS POST DATA
=================
Escape all user input that can be entered in text fields
"""
if 'utm_campaign' in request.POST:
utm_campaign = MySQLdb._mysql.escape_string(
request.POST['utm_campaign'])
if 'start_time' in request.POST:
start_time = MySQLdb._mysql.escape_string(
request.POST['start_time'].strip())
if not (TP.is_timestamp(start_time, 1)) and not (TP.is_timestamp(
start_time, 2)):
err_msg = 'Incorrectly formatted start timestamp.'
raise Exception()
if 'end_time' in request.POST:
end_time = MySQLdb._mysql.escape_string(
request.POST['end_time'].strip())
if not (TP.is_timestamp(end_time, 1)) and not (TP.is_timestamp(
end_time, 2)):
err_msg = 'Incorrectly formatted end timestamp.'
raise Exception()
if 'iso_filter' in request.POST:
country = MySQLdb._mysql.escape_string(request.POST['iso_filter'])
else:
country = '.{2}'
if 'measure_confidence' in request.POST:
if cmp(request.POST['measure_confidence'], 'yes') == 0:
measure_confidence = True
else:
measure_confidence = False
else:
measure_confidence = False
if 'one_step' in request.POST:
if cmp(request.POST['one_step'], 'yes') == 0:
use_one_step = True
else:
use_one_step = False
else:
use_one_step = False
if 'donations_only' in request.POST:
if cmp(request.POST['donations_only'], 'yes') == 0:
donations_only = True
else:
donations_only = False
else:
donations_only = False
""" Convert timestamp format if necessary """
if TP.is_timestamp(start_time, 2):
start_time = TP.timestamp_convert_format(start_time, 2, 1)
if TP.is_timestamp(end_time, 2):
end_time = TP.timestamp_convert_format(end_time, 2, 1)
""" =============================================== """
"""
GENERATE A REPORT SUMMARY TABLE
===============================
"""
if donations_only:
srl = DL.SummaryReportingLoader(
query_type=FDH._TESTTYPE_DONATIONS_)
else:
srl = DL.SummaryReportingLoader(
query_type=FDH._TESTTYPE_BANNER_LP_)
srl.run_query(start_time,
end_time,
utm_campaign,
min_views=-1,
country=country)
column_names = srl.get_column_names()
summary_results = srl.get_results()
if not (summary_results):
html_table = '<h3>No artifact summary data available for %s.</h3>' % utm_campaign
else:
summary_results_list = list()
for row in summary_results:
summary_results_list.append(list(row))
summary_results = summary_results_list
"""
Format results to encode html table cell markup in results
"""
if measure_confidence:
ret = DR.ConfidenceReporting(
query_type='', hyp_test='').get_confidence_on_time_range(
start_time,
end_time,
utm_campaign,
one_step=use_one_step,
country=country) # first get color codes on confidence
conf_colour_code = ret[0]
for row_index in range(len(summary_results)):
artifact_index = summary_results[row_index][
0] + '-' + summary_results[row_index][
1] + '-' + summary_results[row_index][2]
for col_index in range(len(column_names)):
is_coloured_cell = False
if column_names[col_index] in conf_colour_code.keys():
if artifact_index in conf_colour_code[
column_names[col_index]].keys():
summary_results[row_index][
col_index] = '<td style="background-color:' + conf_colour_code[
column_names[col_index]][
artifact_index] + ';">' + str(
summary_results[row_index]
[col_index]) + '</td>'
is_coloured_cell = True
if not (is_coloured_cell):
summary_results[row_index][
col_index] = '<td>' + str(
summary_results[row_index]
[col_index]) + '</td>'
html_table = DR.DataReporting()._write_html_table(
summary_results,
column_names,
use_standard_metric_names=True,
omit_cell_markup=True)
else:
html_table = DR.DataReporting()._write_html_table(
summary_results,
column_names,
use_standard_metric_names=True)
""" Generate totals only if it's a non-donation-only query """
if donations_only:
srl = DL.SummaryReportingLoader(
query_type=FDH._QTYPE_TOTAL_DONATIONS_)
else:
srl = DL.SummaryReportingLoader(query_type=FDH._QTYPE_TOTAL_)
srl.run_query(start_time,
end_time,
utm_campaign,
min_views=-1,
country=country)
total_summary_results = srl.get_results()
if not (total_summary_results):
html_table = html_table + '<div class="spacer"></div><div class="spacer"></div><h3>No data available for %s Totals.</h3>' % utm_campaign
else:
html_table = html_table + '<div class="spacer"></div><div class="spacer"></div>' + DR.DataReporting(
)._write_html_table(total_summary_results,
srl.get_column_names(),
use_standard_metric_names=True)
metric_legend_table = DR.DataReporting().get_standard_metrics_legend()
conf_legend_table = DR.ConfidenceReporting(
query_type='bannerlp',
hyp_test='TTest').get_confidence_legend_table()
html_table = '<h4><u>Metrics Legend:</u></h4><div class="spacer"></div>' + metric_legend_table + \
'<div class="spacer"></div><h4><u>Confidence Legend for Hypothesis Testing:</u></h4><div class="spacer"></div>' + conf_legend_table + '<div class="spacer"></div><div class="spacer"></div>' + html_table
"""
DETERMINE PAYMENT METHODS
=========================
"""
ccl = DL.CiviCRMLoader()
pm_data_counts, pm_data_conversions = ccl.get_payment_methods(
utm_campaign, start_time, end_time, country=country)
html_table_pm_counts = DR.IntervalReporting(
).write_html_table_from_rowlists(
pm_data_counts, ['Payment Method', 'Portion of Donations (%)'],
'Landing Page')
html_table_pm_conversions = DR.IntervalReporting(
).write_html_table_from_rowlists(pm_data_conversions, [
'Payment Method', 'Visits', 'Conversions', 'Conversion Rate (%)',
'Amount', 'Amount 25'
], 'Landing Page')
html_table = html_table + '<div class="spacer"></div><h4><u>Payment Methods Breakdown:</u></h4><div class="spacer"></div>' + html_table_pm_counts + \
'<div class="spacer"></div><div class="spacer"></div>' + html_table_pm_conversions + '<div class="spacer"></div><div class="spacer"></div>'
return render_to_response('tests/table_summary.html', {
'html_table': html_table,
'utm_campaign': utm_campaign
},
context_instance=RequestContext(request))
except Exception as inst:
if cmp(err_msg, '') == 0:
err_msg = 'Could not generate campaign tabular results.'
return index(request, err_msg=err_msg)
def generate_reporting_objects(test_name, start_time, end_time, campaign,
label_dict, label_dict_full, sample_interval,
test_interval, test_type, metric_types,
one_step_var, country):
""" Labels will always be metric names in this case """
# e.g. labels = {'Static banner':'20101227_JA061_US','Fading banner':'20101228_JAFader_US'}
use_labels_var = True
""" Build reporting objects """
ir_cmpgn = DR.IntervalReporting(use_labels=False,
font_size=20,
plot_type='line',
query_type='campaign',
file_path=projSet.__web_home__ +
'campaigns/static/images/')
"""
DETERMINE DONOR DOLLAR BREAKDOWN
================================
"""
try:
logging.info('')
logging.info('Determining Donations Distribution:')
logging.info('===================================\n')
DR.DonorBracketReporting(query_type=FDH._QTYPE_LP_,
file_path=projSet.__web_home__ +
'tests/static/images/').run(
start_time, end_time, campaign)
except:
pass
"""
DETERMINE CATEGORY DISTRIBUTION
===============================
"""
if (0):
DR.CategoryReporting(file_path=projSet.__web_home__ +
'tests/static/images/').run(
start_time, end_time, campaign)
"""
DETERMINE LANGUAGE BREAKDOWN
============================
"""
html_language = ''
if (1):
logging.info('')
logging.info('Determining Languages Distribution:')
logging.info('===================================\n')
columns, data = DL.CiviCRMLoader().get_donor_by_language(
campaign, start_time, end_time)
html_language = DR.DataReporting()._write_html_table(data, columns)
"""
DETERMINE PAYMENT METHODS
=========================
"""
logging.info('')
logging.info('Determining Payment Methods:')
logging.info('============================\n')
ccl = DL.CiviCRMLoader()
pm_data_counts, pm_data_conversions = ccl.get_payment_methods(
campaign, start_time, end_time, country=country)
html_table_pm_counts = DR.IntervalReporting(
).write_html_table_from_rowlists(
pm_data_counts, ['Payment Method', 'Portion of Donations (%)'],
'Landing Page')
html_table_pm_conversions = DR.IntervalReporting(
).write_html_table_from_rowlists(pm_data_conversions, [
'Payment Method', 'Visits', 'Conversions', 'Conversion Rate (%)',
'Amount', 'Amount 25'
], 'Landing Page')
"""
BUILD REPORTING OBJECTS
=======================
"""
if test_type == FDH._TESTTYPE_BANNER_:
ir = DR.IntervalReporting(use_labels=use_labels_var,
font_size=20,
plot_type='step',
query_type=FDH._QTYPE_BANNER_,
file_path=projSet.__web_home__ +
'tests/static/images/')
link_item = '<a href="http://meta.wikimedia.org/w/index.php?title=Special:NoticeTemplate/view&template=%s">%s</a>'
measured_metric = ['don_per_imp', 'amt_norm_per_imp', 'click_rate']
elif test_type == FDH._TESTTYPE_LP_:
ir = DR.IntervalReporting(use_labels=use_labels_var,
font_size=20,
plot_type='step',
query_type=FDH._QTYPE_LP_,
file_path=projSet.__web_home__ +
'tests/static/images/')
link_item = '<a href="http://meta.wikimedia.org/w/index.php?title=Special:NoticeTemplate/view&template=%s">%s</a>'
measured_metric = ['don_per_view', 'amt_norm_per_view']
elif test_type == FDH._TESTTYPE_BANNER_LP_:
ir = DR.IntervalReporting(use_labels=use_labels_var,
font_size=20,
plot_type='step',
query_type=FDH._QTYPE_BANNER_LP_,
file_path=projSet.__web_home__ +
'tests/static/images/')
link_item = '<a href="http://meta.wikimedia.org/w/index.php?title=Special:NoticeTemplate/view&template=%s">%s</a>'
measured_metric = [
'don_per_imp', 'amt_norm_per_imp', 'don_per_view',
'amt_norm_per_view', 'click_rate'
]
"""
GENERATE PLOTS FOR EACH METRIC OF INTEREST
==========================================
"""
logging.info('')
logging.info('Determining Metric Minutely Counts:')
logging.info('==================================\n')
for metric in metric_types:
ir.run(start_time,
end_time,
sample_interval,
metric,
campaign,
label_dict,
one_step=one_step_var,
country=country)
"""
CHECK THE CAMPAIGN VIEWS AND DONATIONS
======================================
"""
ir_cmpgn.run(start_time,
end_time,
sample_interval,
'views',
campaign, {},
one_step=one_step_var,
country=country)
ir_cmpgn.run(start_time,
end_time,
sample_interval,
'donations',
campaign, {},
one_step=one_step_var,
country=country)
"""
PERFORM HYPOTHESIS TESTING
==========================
"""
logging.info('')
logging.info('Executing Confidence Queries:')
logging.info('============================\n')
column_colours = dict()
confidence = list()
cr = DR.ConfidenceReporting(use_labels=use_labels_var,
font_size=20,
plot_type='line',
hyp_test='t_test',
query_type=test_type,
file_path=projSet.__web_home__ +
'tests/static/images/')
for metric in measured_metric:
ret = cr.run(test_name,
campaign,
metric,
label_dict,
start_time,
end_time,
sample_interval,
one_step=one_step_var,
country=country)
confidence.append(ret[0])
column_colours[metric] = ret[1]
"""
GENERATE A REPORT SUMMARY TABLE
===============================
"""
logging.info('')
logging.info('Generating Summary Report:')
logging.info('=========================\n')
"""
if one_step_var == True:
summary_start_time = DL.CiviCRMLoader().get_earliest_donation(campaign)
else:
summary_start_time = DL.LandingPageTableLoader().get_earliest_campaign_view(campaign)
summary_end_time = DL.CiviCRMLoader().get_latest_donation(campaign)
"""
srl = DL.SummaryReportingLoader(query_type=test_type)
srl.run_query(start_time,
end_time,
campaign,
one_step=one_step_var,
country=country)
columns = srl.get_column_names()
summary_results = srl.get_results()
"""
REMOVED - links to pipeline artifacts, this was broken and should be implemented properly later
"""
""" Get Winners, Losers, and percent increase """
winner = list()
loser = list()
percent_increase = list()
labels = list()
for item_long_name in label_dict:
labels.append(label_dict[item_long_name])
for metric in measured_metric:
ret = srl.compare_artifacts(label_dict.keys(), metric, labels=labels)
winner.append(ret[0])
loser.append(ret[1])
percent_increase.append(ret[2])
""" Compose table for showing artifact """
html_table = DR.DataReporting()._write_html_table(
summary_results,
columns,
coloured_columns=column_colours,
use_standard_metric_names=True)
metric_legend_table = DR.DataReporting().get_standard_metrics_legend()
conf_legend_table = DR.ConfidenceReporting(
query_type='bannerlp', hyp_test='TTest').get_confidence_legend_table()
html_table = '<h4><u>Metrics Legend:</u></h4><div class="spacer"></div>' + metric_legend_table + \
'<div class="spacer"></div><h4><u>Confidence Legend for Hypothesis Testing:</u></h4><div class="spacer"></div>' + conf_legend_table + '<div class="spacer"></div><div class="spacer"></div>' + html_table
""" Generate totals for the test summary """
srl = DL.SummaryReportingLoader(query_type=FDH._QTYPE_TOTAL_)
srl.run_query(start_time,
end_time,
campaign,
one_step=one_step_var,
country=country)
html_table = html_table + '<br><br>' + DR.DataReporting(
)._write_html_table(srl.get_results(),
srl.get_column_names(),
use_standard_metric_names=True)
return [
measured_metric, winner, loser, percent_increase, confidence,
html_table_pm_counts, html_table_pm_conversions, html_language,
html_table
]