blob: 16c804491fbee7d8f4a11758a393ee29bf8f5f8d [file] [log] [blame]
# tko/ code shared by various tko/*.cgi graphing scripts
import cgi, cgitb
import os, sys
import common
from autotest_lib.tko import db, plotgraph, perf
from autotest_lib.client.common_lib import kernel_versions
def add_kernel_jobs(label_pattern):
cmd = "select job_idx from tko_jobs where label like '%s'" % label_pattern
nrows = perf.db_cur.execute(cmd)
return [row[0] for row in perf.db_cur.fetchall()]
def is_filtered_platform(platform, platforms_filter):
if not platforms_filter:
return True
for p in platforms_filter:
if platform.startswith(p):
return True
return False
def get_test_attributes(testrunx):
cmd = ( "select attribute, value from tko_test_attributes"
" where test_idx = %d" % testrunx )
nrows = perf.db_cur.execute(cmd)
return dict(perf.db_cur.fetchall())
def get_antag(testrunx):
attrs = get_test_attributes(testrunx)
return attrs.get('antag', None)
def matching_test_attributes(attrs, required_test_attributes):
if not required_test_attributes:
return True
matches = [attrs[key] == required_test_attributes[key]
for key in attrs if key in required_test_attributes]
return min(matches+[True]) # True if all jointly-existing keys matched
def collect_testruns(jobs, test, test_attributes,
platforms_filter, by_hosts, no_antag):
# get test_runs run #s for 1 test on 1 kernel and some platforms
# TODO: Is jobs list short enough to use directly in 1 sql cmd?
# TODO: add filtering on test series?
runs = {} # platform --> list of test runs
for jobx in jobs:
cmd = ( "select test_idx, machine_idx from tko_tests"
" where job_idx = %s and test = %s" )
args = [jobx, test]
nrows = perf.db_cur.execute(cmd, args)
for testrunx, machx in perf.db_cur.fetchall():
platform, host = perf.machine_idx_to_platform_host(machx)
if by_hosts:
platform += '.'+host
if ( is_filtered_platform(platform, platforms_filter) and
test_attributes) and
(not no_antag or get_antag(testrunx) == '') ):
runs.setdefault(platform, []).append(testrunx)
return runs
def all_tested_platforms(test_runs):
# extract list of all tested platforms from test_runs table
platforms = set()
for kernel in test_runs:
return sorted(platforms)
def divide_twoway_testruns(test_runs, platform):
# partition all twoway runs based on name of antagonist progs
twoway_runs = {}
antagonists = set()
for kernel in test_runs:
runs = {}
for testrunx in test_runs[kernel].get(platform, []):
antag = get_antag(testrunx)
if antag is not None:
runs.setdefault(antag, []).append(testrunx)
twoway_runs[kernel] = runs
return twoway_runs, sorted(antagonists)
def collect_raw_scores(runs, metric):
# get unscaled scores of test runs for 1 test on certain jobs
# arrange them by platform type
platform_scores = {} # platform --> list of perf scores
for platform in runs:
vals = perf.get_metric_at_point(runs[platform], metric)
if vals:
platform_scores[platform] = vals
return platform_scores
def collect_scaled_scores(metric, test_runs, regressed_platforms, relative):
# get scores of test runs for 1 test on some kernels and platforms
# optionally make relative to oldest (?) kernel on that platform
# arrange by plotline (ie platform) for gnuplot
plot_data = {} # platform --> (kernel --> list of perf scores)
baseline = {}
for kernel in sorted(test_runs.keys()):
for platform in test_runs[kernel]:
if not (regressed_platforms is None or
platform in regressed_platforms):
continue # delete results for uninteresting platforms
vals = perf.get_metric_at_point(test_runs[kernel][platform],
if vals:
if relative:
if platform not in baseline:
baseline[platform], std = plotgraph.avg_dev(vals)
vals = [v/baseline[platform] for v in vals]
pdp = plot_data.setdefault(platform, {})
pdp.setdefault(kernel, []).extend(vals)
return plot_data
def collect_twoway_scores(metric, antagonists, twoway_runs, relative):
alone = ''
plot_data = {}
for kernel in twoway_runs:
for test2 in antagonists:
runs = twoway_runs[kernel].get(test2, [])
vals = perf.get_metric_at_point(runs, metric)
plot_data.setdefault(test2, {})
if vals:
plot_data[test2][kernel] = vals
if relative:
vals = plot_data[alone].get(kernel, [])
if vals:
baseline = perf.average(vals)
for test2 in antagonists:
vals = plot_data[test2].get(kernel, [])
vals = [val/baseline for val in vals]
if vals:
plot_data[test2][kernel] = vals
for test2 in antagonists:
if kernel in plot_data[test2]:
del plot_data[test2][kernel]
return plot_data
def find_regressions(kernels, test_runs, metric):
# A test is regressed on some platform if its latest results are
# definitely lower than on the reference kernel.
# Runs for the latest kernel may be underway and incomplete.
# In that case, selectively use next-latest kernel.
# TODO: the next-latest method hurts if latest run is not sorted last,
# or if there are several dev threads
ref = kernels[0]
latest = kernels[-1]
prev = kernels[-2:][0]
scores = {} # kernel --> (platform --> list of perf scores)
for k in [ref, prev, latest]:
if k in test_runs:
scores[k] = collect_raw_scores(test_runs[k], metric)
regressed_platforms = []
for platform in scores[ref]:
if latest in scores and platform in scores[latest]:
k = latest
elif prev in scores and platform in scores[prev]:
k = prev
else: # perhaps due to decay of test machines
k = ref # no regression info avail
ref_avg, ref_std = plotgraph.avg_dev(scores[ref][platform])
avg, std = plotgraph.avg_dev(scores[ k ][platform])
if avg+std < ref_avg-ref_std:
return sorted(regressed_platforms)
def get_testrun_context(testrun):
cmd = ( 'select tko_jobs.label, tko_jobs.tag, tko_tests.subdir,'
' tko_tests.started_time'
' from tko_jobs, tko_tests'
' where tko_jobs.job_idx = tko_tests.job_idx'
' and tko_tests.test_idx = %d' % testrun )
nrows = perf.db_cur.execute(cmd)
assert nrows == 1
row = perf.db_cur.fetchone()
row = [row[0], row[1], row[2], row[3].strftime('%m/%d/%y %H:%M')]
return row
def html_top():
print "Content-Type: text/html\n\n<html><body>"
def abs_rel_link(myurl, passthru):
# link redraws current page with opposite absolute/relative choice
mod_passthru = passthru[:]
if 'absolute' in passthru:
opposite = 'relative'
opposite = 'absolute'
url = '%s?%s' % (myurl, '&'.join(mod_passthru))
return "<a href='%s'> %s </a>" % (url, opposite)
def table_1_metric_all_kernels(plot_data, columns, column_argname,
kernels, kernel_dates,
myurl, filtered_passthru):
# generate html table of graph's numbers
# for 1 benchmark metric over all kernels (rows),
# over various platforms or various antagonists etc (cols).
ref_thresholds = {}
print "<table border=1 cellpadding=3 cellspacing=0>"
print "<tr> <td><b> Kernel </b></td>",
for label in columns:
if not label and column_argname == 'antag':
label = 'no antag'
print "<td><b>", label.replace('_', '<br>_'), "</b></td>"
print "</tr>"
for kernel in kernels:
print "<tr> <td><b>", kernel, "</b>",
if kernel in kernel_dates:
print "<br><small>", kernel_dates[kernel], "</small>"
print "</td>"
for col in columns:
print "<td",
vals = plot_data[col].get(kernel, [])
if not vals:
print "> ?",
(avg, std_dev) = plotgraph.avg_dev(vals)
if col not in ref_thresholds:
ref_thresholds[col] = avg - std_dev
if avg+std_dev < ref_thresholds[col]:
print "bgcolor=pink",
print "> ",
args = filtered_passthru[:]
{column_argname:col, 'kernel':kernel})
print "<a href='%s?%s&runs&attrs'>" % (myurl,
print "<b>%.4g</b>" % avg, "</a><br>",
print "&nbsp; <small> %dr </small>" % len(vals),
print "&nbsp; <small> %.3g </small>" % std_dev,
print "</td>"
print "</tr>\n"
print "</table>"
print "<p> <b>Bold value:</b> Average of this metric, then <br>"
print "number of good test runs, then standard deviation of those runs"
print "<br> Pink if regressed from reference kernel"
def table_all_metrics_1_platform(test_runs, platform, relative):
# TODO: show std dev in cells
# can't mark regressions, since some metrics improve downwards
kernels = perf.sort_kernels(test_runs.keys())
scores = {}
attrs = set()
for kernel in kernels:
testruns = test_runs[kernel].get(platform, [])
if testruns:
d = perf.collect_all_metrics_scores(testruns)
scores[kernel] = d
print "No runs completed on", kernel, "<br>"
attrs = sorted(list(attrs))[:100]
print "<table border=1 cellpadding=4 cellspacing=0>"
print "<tr><td> Metric </td>"
for kernel in kernels:
kernel = kernel.replace("_", "_<br>")
print "<td>", kernel, "</td>"
print "</tr>"
for attr in attrs:
print "<tr>"
print "<td>", attr, "</td>"
baseline = None
for kernel in kernels:
print "<td>",
if kernel in scores and attr in scores[kernel]:
(avg, dev) = plotgraph.avg_dev(scores[kernel][attr])
if baseline and relative:
percent = (avg/baseline - 1)*100
print "%+.1f%%" % percent,
baseline = avg
print "%.4g" % avg,
print "?"
print "</td>"
print "</tr>"
print "</table>"
def table_variants_all_tests(plot_data, columns, colkeys, benchmarks,
myurl, filtered_passthru):
# generate html table of graph's numbers
# for primary metric over all benchmarks (rows),
# on one platform and one kernel,
# over various combos of test run attribute constraints (cols).
ref_thresholds = {}
print "<table border=1 cellpadding=3 cellspacing=0>"
print "<tr> <td><b> Benchmark </b></td>",
for col in columns:
print "<td><b>", colkeys[col].replace(',', ',<br>'), "</b></td>"
print "</tr>"
for benchmark in benchmarks:
print "<tr> <td><b>", benchmark, "</b></td>"
for col in columns:
print "<td>",
vals = plot_data[col].get(benchmark, [])
if not vals:
print "?",
(avg, std_dev) = plotgraph.avg_dev(vals)
args = filtered_passthru[:]
perf.append_cgi_args(args, {'test':benchmark})
for keyval in colkeys[col].split(','):
key, val = keyval.split('=', 1)
perf.append_cgi_args(args, {key:val})
print "<a href='%s?%s&runs&attrs'>" % (myurl,
print "<b>%.4g</b>" % avg, "</a><br>",
print "&nbsp; <small> %dr </small>" % len(vals),
print "&nbsp; <small> %.3g </small>" % std_dev,
print "</td>"
print "</tr>\n"
print "</table>"
print "<p> <b>Bold value:</b> Average of this metric, then <br>"
print "number of good test runs, then standard deviation of those runs"
def table_testrun_details(runs, metric, tko_server, show_attrs):
print "<table border=1 cellpadding=4 cellspacing=0>"
print "<tr><td> %s metric </td>" % metric
print "<td> Job label </td> <td> Job tag </td> <td> Run results </td>"
print "<td> Started_time </td>"
if show_attrs:
print "<td> Test attributes </td>"
print "</tr>\n"
for testrunx in runs:
print "<tr> <td>",
vals = perf.get_metric_at_point([testrunx], metric)
for v in vals:
print "%.4g&nbsp;" % v,
print "</td>"
row = get_testrun_context(testrunx)
row[2] = ( "<a href='//%s/results/%s/%s/results/keyval'> %s </a>"
% (tko_server, row[1], row[2], row[2]) )
for v in row:
print "<td> %s </td>" % v
if show_attrs:
attrs = get_test_attributes(testrunx)
print "<td>",
for attr in sorted(attrs.keys()):
if attr == "sysinfo-cmdline": continue
if attr[:4] == "svs-": continue
val = attrs[attr]
if len(val) > 40:
val = val[:40-3] + "..."
print "%s=%s &nbsp; &nbsp; " % (attr, val)
print "</td>"
print "</tr>\n"
print "</table>"
def overview_thumb(test, metric, myurl, passthru):
pass_ = passthru + ['test=%s' % test]
if metric:
pass_ += ['metric=%s' % metric]
pass_ = '&'.join(pass_)
print "<a href='%s?%s&table'>" % (myurl, pass_)
print " <img src='%s?%s&size=450,500'> </a>" % (myurl, pass_)
# embedded graphs fit 3 across on 1400x1050 laptop
def graph_1_test(title, metric, plot_data, line_argname, lines,
kernel_legend, relative, size, dark=False):
# generate graph image for one benchmark, showing avg and
# std dev of one metric, over various kernels (X columns),
# over various platforms or antagonists etc (graphed lines)
xlegend = kernel_legend
ylegend = metric.capitalize()
if relative:
ylegend += ', Relative'
ymin = 0.8
ymin = None
if len(lines) > 1:
keytitle = line_argname.capitalize() + ':'
keytitle = ''
graph = plotgraph.gnuplot(title, xlegend, ylegend, size=size,
xsort=perf.sort_kernels, keytitle=keytitle)
for line in lines:
label = line
if not label and line_argname == 'antag':
label = 'no antag'
graph.add_dataset(label, plot_data[line])
graph.plot(cgi_header=True, ymin=ymin, dark=dark)
def graph_variants_all_tests(title, plot_data, linekeys, size, dark):
# generate graph image showing all benchmarks
# on one platform and one kernel,
# over various combos of test run attribute constraints (lines).
xlegend = "Benchmark"
ylegend = "Relative Perf"
graph = plotgraph.gnuplot(title, xlegend, ylegend, size=size)
for i in linekeys:
graph.add_dataset(linekeys[i], plot_data[i])
graph.plot(cgi_header=True, dark=dark, ymin=0.8)
class generate_views(object):
def __init__(self, kernel_legend, benchmarks, test_group,
site_benchmark_metrics, tko_server,
jobs_selector, no_antag):
self.kernel_legend = kernel_legend
self.benchmarks = benchmarks
self.test_group = test_group
self.tko_server = tko_server
self.jobs_selector = jobs_selector
self.no_antag = no_antag
test, antagonists = self.parse_most_cgi_args()
for b in site_benchmark_metrics:
perf.add_benchmark_main_metric(b, site_benchmark_metrics[b])
self.test_runs = {} # kernel --> (platform --> list of test runs)
self.job_table = {} # kernel id --> list of job idxs
self.kernel_dates = {} # kernel id --> date of nightly test
vary = self.cgiform.getlist('vary')
if vary:
platform = self.platforms_filter[0]
self.analyze_variants_all_tests_1_platform(platform, vary)
elif test:
self.analyze_1_test(test, antagonists)
self.overview_page_all_tests(self.benchmarks, antagonists)
def collect_all_testruns(self, trimmed_kernels, test):
# get test_runs run #s for 1 test on some kernels and platforms
for kernel in trimmed_kernels:
runs = collect_testruns(self.job_table[kernel], test,
self.test_attributes, self.platforms_filter,
'by_hosts' in self.toggles, self.no_antag)
if runs:
self.test_runs[kernel] = runs
def table_for_graph_1_test(self, title, metric, plot_data,
column_argname, columns, filtered_passthru):
# generate detailed html page with 1 graph and corresp numbers
# for 1 benchmark metric over all kernels (rows),
# over various platforms or various antagonists etc (cols).
print '<h3> %s </h3>' % title
print ('%s, machine group %s on //%s server <br>' %
(self.kernel_legend, self.test_group, self.tko_server))
if self.test_tag:
print '%s test script series <br>' % self.test_tag[1:]
print "<img src='%s?%s'>" % (self.myurl, '&'.join(self.passthru))
link = abs_rel_link(self.myurl, self.passthru+['table'])
print "<p><p> <h4> Redraw this with %s performance? </h4>" % link
heading = "%s, %s metric" % (title, metric)
if self.relative:
heading += ", relative"
print "<p><p> <h3> %s: </h3>" % heading
table_1_metric_all_kernels(plot_data, columns, column_argname,
self.kernels, self.kernel_dates,
self.myurl, filtered_passthru)
print "</body></html>"
def graph_1_test_all_platforms(self, test, metric, platforms, plot_data):
# generate graph image for one benchmark
title = test.capitalize()
if 'regress' in self.toggles:
title += ' Regressions'
if 'table' in self.cgiform:
self.table_for_graph_1_test(title, metric, plot_data,
'platforms', platforms,
graph_1_test(title, metric, plot_data, 'platforms', platforms,
self.kernel_legend, self.relative,
self.size, 'dark' in self.toggles)
def testrun_details(self, title, runs, metric):
print '<h3> %s </h3>' % title
print ('%s, machine group %s on //%s server' %
(self.kernel_legend, self.test_group, self.tko_server))
if self.test_tag:
print '<br> %s test script series' % self.test_tag[1:]
print '<p>'
table_testrun_details(runs, metric,
self.tko_server, 'attrs' in self.cgiform)
print "</body></html>"
def testrun_details_for_1_test_kernel_platform(self, test,
metric, platform):
default_kernel = min(self.test_runs.keys())
kernel = self.cgiform.getvalue('kernel', default_kernel)
title = '%s on %s using %s' % (test.capitalize(), platform, kernel)
runs = self.test_runs[kernel].get(platform, [])
self.testrun_details(title, runs, metric)
def analyze_1_metric_all_platforms(self, test, metric):
if 'regress' in self.toggles:
regressed_platforms = find_regressions(self.kernels, self.test_runs,
regressed_platforms = None
plot_data = collect_scaled_scores(metric, self.test_runs,
regressed_platforms, self.relative)
platforms = sorted(plot_data.keys())
if not plot_data:
print 'No runs'
elif 'runs' in self.cgiform:
self.testrun_details_for_1_test_kernel_platform(test, metric,
self.graph_1_test_all_platforms(test, metric, platforms, plot_data)
def analyze_all_metrics_1_platform(self, test, platform):
# TODO: show #runs in header
heading = "%s %s:&nbsp %s" % (self.test_group, self.kernel_legend,
print "<h2> %s </h2>" % heading
print "platform=%s <br>" % platform
for attr in self.test_attributes:
print "%s=%s &nbsp; " % (attr, self.test_attributes[attr])
print "<p>"
table_all_metrics_1_platform(self.test_runs, platform, self.relative)
print "</body></html>"
def table_for_variants_all_tests(self, title, plot_data, colkeys, columns,
filtered_passthru, test_tag):
# generate detailed html page with 1 graph and corresp numbers
# for primary metric over all benchmarks (rows),
# on one platform and one kernel,
# over various combos of test run attribute constraints (cols).
print '<h3> %s </h3>' % title
print ('%s, machine group %s on //%s server <br>' %
(self.kernel_legend, self.test_group, self.tko_server))
if test_tag:
print '%s test script series <br>' % test_tag[1:]
varies = ['vary='+colkeys[col] for col in columns]
print "<img src='%s?%s'>" % (self.myurl, '&'.join(self.passthru+varies))
print "<p><p> <h3> %s: </h3>" % title
table_variants_all_tests(plot_data, columns, colkeys, self.benchmarks,
self.myurl, filtered_passthru)
print "</body></html>"
def analyze_variants_all_tests_1_platform(self, platform, vary):
# generate one graph image for results of all benchmarks
# on one platform and one kernel, comparing effects of
# two or more combos of kernel options (test run attributes)
# (numa_fake,stale_page,kswapd_merge,sched_idle, etc)
kernel = self.cgiform.getvalue('kernel', 'some_kernel')
self.passthru.append('kernel=%s' % kernel)
# two or more vary_groups, one for each plotted line,
# each group begins with vary= and ends with next &
# each group has comma-separated list of test attribute key=val pairs
# eg vary=keyval1,keyval2&vary=keyval3,keyval4
vary_groups = [dict(pair.split('=',1) for pair
in vary_group.split(','))
for vary_group in vary]
test = self.benchmarks[0] # pick any test in all jobs
kernels, test_tag = self.jobs_selector(test, self.job_table,
linekeys = {}
plot_data = {}
baselines = {}
for i, vary_group in enumerate(vary_groups):
group_attributes = self.test_attributes.copy()
linekey = ','.join('%s=%s' % (attr, vary_group[attr])
for attr in vary_group)
linekeys[i] = linekey
data = {}
for benchmark in self.benchmarks:
metric = perf.benchmark_main_metric(benchmark)
runs = collect_testruns(self.job_table[kernel],
'by_hosts' in self.toggles,
vals = []
for testrunx in runs[platform]:
vals += perf.get_metric_at_point([testrunx], metric)
if vals:
if benchmark not in baselines:
baselines[benchmark], stddev = plotgraph.avg_dev(vals)
vals = [val/baselines[benchmark] for val in vals]
data[benchmark] = vals
plot_data[i] = data
title = "%s on %s" % (kernel, platform)
for attr in self.test_attributes:
title += ', %s=%s' % (attr, self.test_attributes[attr])
if 'table' in self.cgiform:
self.table_for_variants_all_tests(title, plot_data, linekeys,
graph_variants_all_tests(title, plot_data, linekeys,
self.size, 'dark' in self.toggles)
def graph_twoway_antagonists_1_test_1_platform(
self, test, metric, platform, antagonists, twoway_runs):
# generate graph of one benchmark's performance paired with
# various antagonists, with one plotted line per antagonist,
# over most kernels (X axis), all on one machine type
# performance is relative to the no-antag baseline case
plot_data = collect_twoway_scores(metric, antagonists,
twoway_runs, self.relative)
title = "%s vs. an Antagonist on %s:" % (test.capitalize(), platform)
if 'table' in self.cgiform:
filtered_passthru = [arg for arg in self.passthru
if not arg.startswith('antag=')]
self.table_for_graph_1_test(title, metric, plot_data,
'antag', antagonists,
graph_1_test(title, metric, plot_data, 'antag', antagonists,
self.kernel_legend, self.relative,
self.size, 'dark' in self.toggles)
def testrun_details_for_twoway_test(self, test, metric, platform,
antagonist, twoway_runs):
default_kernel = min(twoway_runs.keys())
kernel = self.cgiform.getvalue('kernel', default_kernel)
title = '%s vs. Antagonist %s on %s using %s' % (
test.capitalize(), antagonist.capitalize(), platform, kernel)
runs = twoway_runs[kernel].get(antagonist, [])
self.testrun_details(title, runs, metric)
def analyze_twoway_antagonists_1_test_1_platform(
self, test, metric, platform, antagonists):
twoway_runs, all_antagonists = divide_twoway_testruns(self.test_runs,
if antagonists == ['*']:
antagonists = all_antagonists
if not twoway_runs:
print 'No runs'
elif 'runs' in self.cgiform:
test, metric, platform, antagonists[0], twoway_runs)
test, metric, platform, antagonists, twoway_runs)
def get_twoway_default_platform(self):
if self.platforms_filter:
return self.platforms_filter[0]
test = 'unixbench'
kernels, test_tag = self.jobs_selector(test, self.job_table,
self.collect_all_testruns(kernels, test+test_tag)
return all_tested_platforms(self.test_runs)[0]
def overview_page_all_tests(self, benchmarks, antagonists):
# generate overview html page with small graphs for each benchmark
# linking to detailed html page for that benchmark
# recursively link to this same cgi to generate each image
if antagonists is not None:
heading = ('Twoway Container Isolation using %s on %s' %
(self.kernel_legend, self.get_twoway_default_platform()))
heading = '%s, %s Benchmarks' % (self.kernel_legend,
if 'regress' in self.toggles:
heading += ", Regressions Only"
print "<h3> %s </h3>" % heading
for test in benchmarks:
overview_thumb(test, '', self.myurl, self.passthru)
if test == 'unixbench':
overview_thumb('unixbench', 'Process_creation',
self.myurl, self.passthru)
link = abs_rel_link(self.myurl, self.passthru)
print "<p><p> <h4> Redraw this with %s performance? </h4>" % link
print "</body></html>"
def analyze_1_test(self, test, antagonists):
self.passthru.append('test=%s' % test)
metric = self.cgiform.getvalue('metric', '')
if metric:
self.passthru.append('metric=%s' % metric)
metric = perf.benchmark_main_metric(test)
assert metric, "no default metric for test %s" % test
self.kernels, self.test_tag = self.jobs_selector(test, self.job_table,
self.collect_all_testruns(self.kernels, test+self.test_tag)
if not self.platforms_filter and (metric == '*' or
antagonists is not None):
# choose default platform
self.platforms_filter = all_tested_platforms(self.test_runs)[0:1]
self.passthru.append('platforms=%s' %
if antagonists is not None:
antagonists = antagonists.split(',')
if len(antagonists) == 1 and antagonists != ['*']:
self.relative = False
test, metric, self.platforms_filter[0], antagonists)
elif metric == '*':
platform = self.platforms_filter[0]
self.analyze_all_metrics_1_platform(test, platform)
self.analyze_1_metric_all_platforms(test, metric)
def parse_most_cgi_args(self):
self.myurl = os.path.basename(sys.argv[0])
self.cgiform = cgi.FieldStorage(keep_blank_values=True)
self.size = self.cgiform.getvalue('size', '1200,850')
all_toggles = set(('absolute', 'regress', 'dark', 'by_hosts'))
self.toggles = set(tog for tog in all_toggles if tog in self.cgiform)
platforms = self.cgiform.getvalue('platforms', '')
if '.' in platforms:
self.passthru = list(self.toggles)
self.relative = 'absolute' not in self.toggles
if platforms:
self.passthru.append('platforms=%s' % platforms)
self.platforms_filter = platforms.split(',')
self.platforms_filter = []
self.test_attributes = perf.parse_test_attr_args(self.cgiform)
perf.append_cgi_args(self.passthru, self.test_attributes)
test = self.cgiform.getvalue('test', '')
if 'antag' in self.cgiform:
antagonists = ','.join(self.cgiform.getlist('antag'))
# antag=*
# or antag=test1,test2,test3,...
# or antag=test1&antag=test2&...
# testN is empty for solo case of no antagonist
self.passthru.append('antag=%s' % antagonists)
antagonists = None # not same as ''
return test, antagonists