forked from llvm-mirror/lnt
/
views.py
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/
views.py
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import datetime
import os
import re
import tempfile
import time
import flask
from flask import abort
from flask import current_app
from flask import g
from flask import make_response
from flask import redirect
from flask import render_template
from flask import request
from flask import url_for
import sqlalchemy.sql
import lnt.util
import lnt.util.ImportData
import lnt.util.stats
from lnt.server.ui.globals import db_url_for, v4_url_for
import lnt.server.reporting.analysis
import lnt.server.reporting.runs
from lnt.server.ui.decorators import frontend, db_route, v4_route
import lnt.server.ui.util
import lnt.server.reporting.dailyreport
import lnt.server.reporting.summaryreport
integral_rex = re.compile(r"[\d]+")
###
# Root-Only Routes
@frontend.route('/favicon.ico')
def favicon_ico():
return redirect(url_for('.static', filename='favicon.ico'))
@frontend.route('/select_db')
def select_db():
path = request.args.get('path')
db = request.args.get('db')
if path is None:
abort(400)
if db not in current_app.old_config.databases:
abort(404)
# Rewrite the path.
new_path = "/db_%s" % db
if not path.startswith("/db_"):
new_path += path
else:
if '/' in path[1:]:
new_path += "/" + path.split("/", 2)[2]
return redirect(request.script_root + new_path)
#####
# Per-Database Routes
@db_route('/', only_v3 = False)
def index():
return render_template("index.html")
###
# Database Actions
@db_route('/submitRun', only_v3=False, methods=('GET', 'POST'))
def submit_run():
if request.method == 'POST':
input_file = request.files.get('file')
input_data = request.form.get('input_data')
commit = int(request.form.get('commit', 0))
if input_file and not input_file.content_length:
input_file = None
if not input_file and not input_data:
return render_template(
"submit_run.html", error="must provide input file or data")
if input_file and input_data:
return render_template(
"submit_run.html", error="cannot provide input file *and* data")
if input_file:
data_value = input_file.read()
else:
data_value = input_data
# Stash a copy of the raw submission.
#
# To keep the temporary directory organized, we keep files in
# subdirectories organized by (database, year-month).
utcnow = datetime.datetime.utcnow()
tmpdir = os.path.join(current_app.old_config.tempDir, g.db_name,
"%04d-%02d" % (utcnow.year, utcnow.month))
try:
os.makedirs(tmpdir)
except OSError,e:
pass
# Save the file under a name prefixed with the date, to make it easier
# to use these files in cases we might need them for debugging or data
# recovery.
prefix = utcnow.strftime("data-%Y-%m-%d_%H-%M-%S")
fd,path = tempfile.mkstemp(prefix=prefix, suffix='.plist',
dir=str(tmpdir))
os.write(fd, data_value)
os.close(fd)
# Get a DB connection.
db = request.get_db()
# Import the data.
#
# FIXME: Gracefully handle formats failures and DOS attempts. We
# should at least reject overly large inputs.
result = lnt.util.ImportData.import_and_report(
current_app.old_config, g.db_name, db, path, '<auto>', commit)
return flask.jsonify(**result)
return render_template("submit_run.html")
###
# V4 Schema Viewer
@v4_route("/")
def v4_overview():
return render_template("v4_overview.html",
testsuite_name=g.testsuite_name)
@v4_route("/recent_activity")
def v4_recent_activity():
ts = request.get_testsuite()
# Get the most recent runs in this tag, we just arbitrarily limit to looking
# at the last 100 submission.
recent_runs = ts.query(ts.Run).\
order_by(ts.Run.start_time.desc()).limit(100)
recent_runs = list(recent_runs)
# Compute the active machine list.
active_machines = dict((run.machine.name, run)
for run in recent_runs[::-1])
# Compute the active submission list.
#
# FIXME: Remove hard coded field use here.
N = 30
active_submissions = [(r, r.order.llvm_project_revision)
for r in recent_runs[:N]]
return render_template("v4_recent_activity.html",
testsuite_name=g.testsuite_name,
active_machines=active_machines,
active_submissions=active_submissions)
@v4_route("/machine/<int:id>")
def v4_machine(id):
# Compute the list of associated runs, grouped by order.
from lnt.server.ui import util
# Gather all the runs on this machine.
ts = request.get_testsuite()
associated_runs = util.multidict(
(run_order, r)
for r,run_order in ts.query(ts.Run, ts.Order).\
join(ts.Order).\
filter(ts.Run.machine_id == id).\
order_by(ts.Run.start_time.desc()))
associated_runs = associated_runs.items()
associated_runs.sort()
return render_template("v4_machine.html",
testsuite_name=g.testsuite_name, id=id,
associated_runs=associated_runs)
class V4RequestInfo(object):
def __init__(self, run_id, only_html_body=True):
self.db = request.get_db()
self.ts = ts = request.get_testsuite()
self.run = run = ts.query(ts.Run).filter_by(id=run_id).first()
if run is None:
abort(404)
# Get the aggregation function to use.
aggregation_fn_name = request.args.get('aggregation_fn')
self.aggregation_fn = { 'min' : min,
'median' : lnt.util.stats.median }.get(
aggregation_fn_name, min)
# Find the neighboring runs, by order.
prev_runs = list(ts.get_previous_runs_on_machine(run, N = 3))
next_runs = list(ts.get_next_runs_on_machine(run, N = 3))
self.neighboring_runs = next_runs[::-1] + [self.run] + prev_runs
# Select the comparison run as either the previous run, or a user
# specified comparison run.
compare_to_str = request.args.get('compare_to')
if compare_to_str:
compare_to_id = int(compare_to_str)
self.compare_to = ts.query(ts.Run).\
filter_by(id=compare_to_id).first()
if self.compare_to is None:
# FIXME: Need better way to report this error.
abort(404)
self.comparison_neighboring_runs = (
list(ts.get_next_runs_on_machine(self.compare_to, N=3))[::-1] +
[self.compare_to] +
list(ts.get_previous_runs_on_machine(self.compare_to, N=3)))
else:
if prev_runs:
self.compare_to = prev_runs[0]
else:
self.compare_to = None
self.comparison_neighboring_runs = self.neighboring_runs
try:
self.num_comparison_runs = int(
request.args.get('num_comparison_runs'))
except:
self.num_comparison_runs = 10
# Find the baseline run, if requested.
baseline_str = request.args.get('baseline')
if baseline_str:
baseline_id = int(baseline_str)
self.baseline = ts.query(ts.Run).\
filter_by(id=baseline_id).first()
if self.baseline is None:
# FIXME: Need better way to report this error.
abort(404)
else:
self.baseline = None
# Gather the runs to use for statistical data.
comparison_start_run = self.compare_to or self.run
self.comparison_window = list(ts.get_previous_runs_on_machine(
comparison_start_run, self.num_comparison_runs))
reports = lnt.server.reporting.runs.generate_run_report(
self.run, baseurl=db_url_for('index', _external=True),
only_html_body=only_html_body, result=None,
compare_to=self.compare_to, baseline=self.baseline,
comparison_window=self.comparison_window,
aggregation_fn=self.aggregation_fn)
_, self.text_report, self.html_report, self.sri = reports
@v4_route("/<int:id>/report")
def v4_report(id):
info = V4RequestInfo(id, only_html_body=False)
return make_response(info.html_report)
@v4_route("/<int:id>/text_report")
def v4_text_report(id):
info = V4RequestInfo(id, only_html_body=False)
response = make_response(info.text_report)
response.mimetype = "text/plain"
return response
# Compatilibity route for old run pages.
@db_route("/simple/<tag>/<int:id>/", only_v3=False)
def simple_run(tag, id):
# Attempt to find a V4 run which declares that it matches this simple run
# ID. We do this so we can preserve some URL compatibility for old
# databases.
if g.db_info.db_version != '0.4':
return render_template("error.html", message="""\
Invalid URL for version %r database.""" % (g.db_info.db_version,))
# Get the expected test suite.
db = request.get_db()
ts = db.testsuite[tag]
# Look for a matched run.
matched_run = ts.query(ts.Run).\
filter(ts.Run.simple_run_id == id).\
first()
# If we found one, redirect to it's report.
if matched_run is not None:
return redirect(db_url_for("v4_run", testsuite_name=tag,
id=matched_run.id))
# Otherwise, report an error.
return render_template("error.html", message="""\
Unable to find a v0.4 run for this ID. Please use the native v0.4 URL interface
(instead of the /simple/... URL schema).""")
@v4_route("/<int:id>")
def v4_run(id):
info = V4RequestInfo(id)
ts = info.ts
run = info.run
# Parse the view options.
options = {}
options['show_delta'] = bool(request.args.get('show_delta'))
options['show_previous'] = bool(request.args.get('show_previous'))
options['show_stddev'] = bool(request.args.get('show_stddev'))
options['show_mad'] = bool(request.args.get('show_mad'))
options['show_all'] = bool(request.args.get('show_all'))
options['show_all_samples'] = bool(request.args.get('show_all_samples'))
options['show_sample_counts'] = bool(request.args.get('show_sample_counts'))
options['show_graphs'] = show_graphs = bool(request.args.get('show_graphs'))
options['show_data_table'] = bool(request.args.get('show_data_table'))
options['hide_report_by_default'] = bool(
request.args.get('hide_report_by_default'))
options['num_comparison_runs'] = info.num_comparison_runs
options['test_filter'] = test_filter_str = request.args.get(
'test_filter', '')
if test_filter_str:
test_filter_re = re.compile(test_filter_str)
else:
test_filter_re = None
options['test_min_value_filter'] = test_min_value_filter_str = \
request.args.get('test_min_value_filter', '')
if test_min_value_filter_str != '':
test_min_value_filter = float(test_min_value_filter_str)
else:
test_min_value_filter = 0.0
options['aggregation_fn'] = request.args.get('aggregation_fn', 'min')
# Get the test names.
test_info = ts.query(ts.Test.name, ts.Test.id).\
order_by(ts.Test.name).all()
# Filter the list of tests by name, if requested.
if test_filter_re:
test_info = [test
for test in test_info
if test_filter_re.search(test[0])]
return render_template(
"v4_run.html", ts=ts, options=options,
primary_fields=list(ts.Sample.get_primary_fields()),
test_info=test_info, analysis=lnt.server.reporting.analysis,
test_min_value_filter=test_min_value_filter,
request_info=info)
@v4_route("/order/<int:id>")
def v4_order(id):
# Get the testsuite.
ts = request.get_testsuite()
# Get the order.
order = ts.query(ts.Order).filter(ts.Order.id == id).first()
if order is None:
abort(404)
return render_template("v4_order.html", ts=ts, order=order)
@v4_route("/all_orders")
def v4_all_orders():
# Get the testsuite.
ts = request.get_testsuite()
# Get the orders.
orders = ts.query(ts.Order).all()
# Order the runs totally.
orders.sort()
return render_template("v4_all_orders.html", ts=ts, orders=orders)
@v4_route("/<int:id>/graph")
def v4_run_graph(id):
# This is an old style endpoint that treated graphs as associated with
# runs. Redirect to the new endpoint.
ts = request.get_testsuite()
run = ts.query(ts.Run).filter_by(id=id).first()
if run is None:
abort(404)
# Convert the old style test parameters encoding.
args = { 'highlight_run' : id }
plot_number = 0
for name,value in request.args.items():
# If this isn't a test specification, just forward it.
if not name.startswith('test.'):
args[name] = value
continue
# Otherwise, rewrite from the old style of::
#
# test.<test id>=<sample field index>
#
# into the new style of::
#
# plot.<number>=<machine id>.<test id>.<sample field index>
test_id = name.split('.', 1)[1]
args['plot.%d' % (plot_number,)] = '%d.%s.%s' % (
run.machine.id, test_id, value)
plot_number += 1
return redirect(v4_url_for("v4_graph", **args))
@v4_route("/graph")
def v4_graph():
from lnt.server.ui import util
from lnt.testing import PASS
from lnt.util import stats
from lnt.external.stats import stats as ext_stats
ts = request.get_testsuite()
# Parse the view options.
options = {}
options['hide_lineplot'] = bool(request.args.get('hide_lineplot'))
show_lineplot = not options['hide_lineplot']
options['show_mad'] = show_mad = bool(request.args.get('show_mad'))
options['show_stddev'] = show_stddev = bool(request.args.get('show_stddev'))
options['show_points'] = show_points = bool(request.args.get('show_points'))
options['show_all_points'] = show_all_points = bool(
request.args.get('show_all_points'))
options['show_linear_regression'] = show_linear_regression = bool(
request.args.get('show_linear_regression'))
options['show_failures'] = show_failures = bool(
request.args.get('show_failures'))
options['normalize_by_median'] = normalize_by_median = bool(
request.args.get('normalize_by_median'))
options['show_moving_average'] = moving_average = bool(
request.args.get('show_moving_average'))
options['show_moving_median'] = moving_median = bool(
request.args.get('show_moving_median'))
options['moving_window_size'] = moving_window_size = int(
request.args.get('moving_window_size', 10))
options['hide_highlight'] = bool(
request.args.get('hide_highlight'))
show_highlight = not options['hide_highlight']
def convert_revision(dotted):
"""Turn a version number like 489.2.10 into something
that is ordered and sortable.
For now 489.2.10 will be returned as a tuple of ints.
"""
dotted = integral_rex.findall(dotted)
return tuple([int(d) for d in dotted])
# Load the graph parameters.
graph_parameters = []
for name,value in request.args.items():
# Plots to graph are passed as::
#
# plot.<unused>=<machine id>.<test id>.<field index>
if not name.startswith(str('plot.')):
continue
# Ignore the extra part of the key, it is unused.
machine_id_str,test_id_str,field_index_str = value.split('.')
try:
machine_id = int(machine_id_str)
test_id = int(test_id_str)
field_index = int(field_index_str)
except:
return abort(400)
if not (0 <= field_index < len(ts.sample_fields)):
return abort(400)
machine = ts.query(ts.Machine).filter(ts.Machine.id == machine_id).one()
test = ts.query(ts.Test).filter(ts.Test.id == test_id).one()
field = ts.sample_fields[field_index]
graph_parameters.append((machine, test, field))
# Order the plots by machine name, test name and then field.
graph_parameters.sort(key = lambda (m,t,f): (m.name, t.name, f.name))
# Sanity check the arguments.
if not graph_parameters:
return render_template("error.html", message="Nothing to graph.")
# Create region of interest for run data region if we are performing a
# comparison.
revision_range = None
highlight_run_id = request.args.get('highlight_run')
if show_highlight and highlight_run_id and highlight_run_id.isdigit():
highlight_run = ts.query(ts.Run).filter_by(
id=int(highlight_run_id)).first()
if highlight_run is None:
abort(404)
# Find the neighboring runs, by order.
prev_runs = list(ts.get_previous_runs_on_machine(highlight_run, N = 1))
if prev_runs:
start_rev = prev_runs[0].order.llvm_project_revision
end_rev = highlight_run.order.llvm_project_revision
revision_range = {
"start": convert_revision(start_rev),
"end": convert_revision(end_rev) }
# Build the graph data.
legend = []
graph_plots = []
overview_plots = []
num_plots = len(graph_parameters)
for i,(machine,test,field) in enumerate(graph_parameters):
# Determine the base plot color.
col = list(util.makeDarkColor(float(i) / num_plots))
legend.append((machine, test.name, field.name, tuple(col)))
# Load all the field values for this test on the same machine.
#
# FIXME: Don't join to Order here, aggregate this across all the tests
# we want to load. Actually, we should just make this a single query.
#
# FIXME: Don't hard code field name.
q = ts.query(field.column, ts.Order.llvm_project_revision).\
join(ts.Run).join(ts.Order).\
filter(ts.Run.machine_id == machine.id).\
filter(ts.Sample.test == test).\
filter(field.column != None)
# Unless all samples requested, filter out failing tests.
if not show_failures:
if field.status_field:
q = q.filter((field.status_field.column == PASS) |
(field.status_field.column == None))
# Aggregate by revision.
data = util.multidict((rev, val) for val,rev in q).items()
data.sort(key=lambda sample: convert_revision(sample[0]))
# Compute the graph points.
errorbar_data = []
points_data = []
pts = []
moving_median_data = []
moving_average_data = []
if normalize_by_median:
normalize_by = 1.0/stats.median([min(values)
for _,values in data])
else:
normalize_by = 1.0
for pos, (point_label, orig_values) in enumerate(data):
metadata = {"label":point_label}
# on simple revisions use rev number for x else start from
# 0
rev_x = convert_revision(point_label)
x = rev_x if len(rev_x)==1 else pos
values = [v*normalize_by for v in orig_values]
min_value = min(values)
pts.append((x, min_value, metadata))
# Add the individual points, if requested.
# For each point add a text label for the mouse over.
if show_all_points:
for v in values:
points_data.append((x, v, metadata))
elif show_points:
points_data.append((x, min_value, metadata))
# Add the standard deviation error bar, if requested.
if show_stddev:
mean = stats.mean(values)
sigma = stats.standard_deviation(values)
errorbar_data.append((x, mean, sigma))
# Add the MAD error bar, if requested.
if show_mad:
med = stats.median(values)
mad = stats.median_absolute_deviation(values, med)
errorbar_data.append((x, med, mad))
# Compute the moving average and or moving median of our data if requested.
if moving_average or moving_median:
fun = None
def compute_moving_average(x, window, average_list, median_list):
average_list.append((x, lnt.util.stats.mean(window)))
def compute_moving_median(x, window, average_list, median_list):
median_list.append((x, lnt.util.stats.median(window)))
def compute_moving_average_and_median(x, window, average_list, median_list):
average_list.append((x, lnt.util.stats.mean(window)))
median_list.append((x, lnt.util.stats.median(window)))
if moving_average and moving_median:
fun = compute_moving_average_and_median
elif moving_average:
fun = compute_moving_average
else:
fun = compute_moving_median
len_pts = len(pts)
for i in range(len_pts):
start_index = max(0, i - moving_window_size)
end_index = min(len_pts, i + moving_window_size)
window_pts = [x[1] for x in pts[start_index:end_index]]
fun(pts[i][0], window_pts, moving_average_data, moving_median_data)
# On the overview, we always show the line plot.
overview_plots.append({
"data" : pts,
"color" : util.toColorString(col) })
# Add the minimum line plot, if requested.
if show_lineplot:
graph_plots.append({
"data" : pts,
"color" : util.toColorString(col) })
# Add regression line, if requested.
if show_linear_regression:
xs = [t for t,v,_ in pts]
ys = [v for t,v,_ in pts]
# We compute the regression line in terms of a normalized X scale.
x_min, x_max = min(xs), max(xs)
try:
norm_xs = [(x - x_min) / (x_max - x_min)
for x in xs]
except ZeroDivisionError:
norm_xs = xs
try:
info = ext_stats.linregress(norm_xs, ys)
except ZeroDivisionError:
info = None
except ValueError:
info = None
if info is not None:
slope, intercept,_,_,_ = info
reglin_col = [c * .7 for c in col]
reglin_pts = [(x_min, 0.0 * slope + intercept),
(x_max, 1.0 * slope + intercept)]
graph_plots.insert(0, {
"data" : reglin_pts,
"color" : util.toColorString(reglin_col),
"lines" : {
"lineWidth" : 2 },
"shadowSize" : 4 })
# Add the points plot, if used.
if points_data:
pts_col = (0,0,0)
graph_plots.append({
"data" : points_data,
"color" : util.toColorString(pts_col),
"lines" : {
"show" : False },
"points" : {
"show" : True,
"radius" : .25,
"fill" : True } })
# Add the error bar plot, if used.
if errorbar_data:
bar_col = [c*.7 for c in col]
graph_plots.append({
"data" : errorbar_data,
"lines" : { "show" : False },
"color" : util.toColorString(bar_col),
"points" : {
"errorbars" : "y",
"yerr" : { "show" : True,
"lowerCap" : "-",
"upperCap" : "-",
"lineWidth" : 1 } } })
# Add the moving average plot, if used.
if moving_average_data:
col = [0.32, 0.6, 0.0]
graph_plots.append({
"data" : moving_average_data,
"color" : util.toColorString(col) })
# Add the moving median plot, if used.
if moving_median_data:
col = [0.75, 0.0, 1.0]
graph_plots.append({
"data" : moving_median_data,
"color" : util.toColorString(col) })
return render_template("v4_graph.html", ts=ts, options=options,
revision_range=revision_range,
graph_plots=graph_plots,
overview_plots=overview_plots, legend=legend)
@v4_route("/global_status")
def v4_global_status():
from lnt.server.ui import util
ts = request.get_testsuite()
primary_fields = sorted(list(ts.Sample.get_primary_fields()),
key=lambda f: f.name)
fields = dict((f.name, f) for f in primary_fields)
# Get the latest run.
latest = ts.query(ts.Run.start_time).\
order_by(ts.Run.start_time.desc()).first()
# If we found an entry, use that.
if latest is not None:
latest_date, = latest
else:
# Otherwise, just use today.
latest_date = datetime.date.today()
# Create a datetime for the day before the most recent run.
yesterday = latest_date - datetime.timedelta(days=1)
# Get arguments.
revision = int(request.args.get('revision',
ts.Machine.DEFAULT_BASELINE_REVISION))
field = fields.get(request.args.get('field', None), primary_fields[0])
# Get the list of all runs we might be interested in.
recent_runs = ts.query(ts.Run).filter(ts.Run.start_time > yesterday).all()
# Aggregate the runs by machine.
recent_runs_by_machine = util.multidict()
for run in recent_runs:
recent_runs_by_machine[run.machine] = run
# Get a sorted list of recent machines.
recent_machines = sorted(recent_runs_by_machine.keys(),
key=lambda m: m.name)
# We use periods in our machine names. css does not like this
# since it uses periods to demark classes. Thus we convert periods
# in the names of our machines to dashes for use in css. It is
# also convenient for our computations in the jinja page to have
# access to
def get_machine_keys(m):
m.css_name = m.name.replace('.','-')
return m
recent_machines = map(get_machine_keys, recent_machines)
# For each machine, build a table of the machine, the baseline run, and the
# most recent run. We also computed a list of all the runs we are reporting
# over.
machine_run_info = []
reported_run_ids = []
for machine in recent_machines:
runs = recent_runs_by_machine[machine]
# Get the baseline run for this machine.
baseline = machine.get_closest_previously_reported_run(revision)
# Choose the "best" run to report on. We want the most recent one with
# the most recent order.
run = max(runs, key=lambda r: (r.order, r.start_time))
machine_run_info.append((baseline, run))
reported_run_ids.append(baseline.id)
reported_run_ids.append(run.id)
# Get the set all tests reported in the recent runs.
reported_tests = ts.query(ts.Test.id, ts.Test.name).filter(
sqlalchemy.sql.exists('*', sqlalchemy.sql.and_(
ts.Sample.run_id.in_(reported_run_ids),
ts.Sample.test_id == ts.Test.id))).all()
# Load all of the runs we are interested in.
runinfo = lnt.server.reporting.analysis.RunInfo(ts, reported_run_ids)
# Build the test matrix. This is a two dimensional table index by
# (machine-index, test-index), where each entry is the percent change.
test_table = []
for i,(test_id,test_name) in enumerate(reported_tests):
# Create the row, starting with the test name and worst entry.
row = [(test_id, test_name), None]
# Compute comparison results for each machine.
row.extend((runinfo.get_run_comparison_result(run, baseline, test_id,
field), run.id)
for baseline,run in machine_run_info)
# Compute the worst cell value.
row[1] = max(cr.pct_delta
for cr,_ in row[2:])
test_table.append(row)
# Order the table by worst regression.
test_table.sort(key = lambda row: row[1], reverse=True)
return render_template("v4_global_status.html",
ts=ts,
tests=test_table,
machines=recent_machines,
fields=primary_fields,
selected_field=field,
selected_revision=revision)
@v4_route("/daily_report")
def v4_daily_report_overview():
# Redirect to the report for the most recent submitted run's date.
ts = request.get_testsuite()
# Get the latest run.
latest = ts.query(ts.Run).\
order_by(ts.Run.start_time.desc()).limit(1).first()
# If we found a run, use it's start time.
if latest:
date = latest.start_time
else:
# Otherwise, just use today.
date = datetime.date.today()
return redirect(v4_url_for("v4_daily_report",
year=date.year, month=date.month, day=date.day))
@v4_route("/daily_report/<int:year>/<int:month>/<int:day>")
def v4_daily_report(year, month, day):
num_days_str = request.args.get('num_days')
if num_days_str is not None:
num_days = int(num_days_str)
else:
num_days = 3
day_start_str = request.args.get('day_start')
if day_start_str is not None:
day_start = int(day_start_str)
else:
day_start = 16
ts = request.get_testsuite()
# Create the report object.
report = lnt.server.reporting.dailyreport.DailyReport(
ts, year, month, day, num_days, day_start)
# Build the report.
report.build()
return render_template("v4_daily_report.html", ts=ts, report=report,
analysis=lnt.server.reporting.analysis)
###
# Cross Test-Suite V4 Views
def get_summary_config_path():
return os.path.join(current_app.old_config.tempDir,
'summary_report_config.json')
@db_route("/summary_report/edit", only_v3=False, methods=('GET', 'POST'))
def v4_summary_report_ui():
# If this is a POST request, update the saved config.
if request.method == 'POST':
# Parse the config data.
config_data = request.form.get('config')
config = flask.json.loads(config_data)
# Write the updated config.
with open(get_summary_config_path(), 'w') as f:
flask.json.dump(config, f, indent=2)
# Redirect to the summary report.
return redirect(db_url_for("v4_summary_report"))
config_path = get_summary_config_path()
if os.path.exists(config_path):
with open(config_path) as f:
config = flask.json.load(f)
else:
config = {
"machine_names" : [],
"orders" : [],
"machine_patterns" : [],
}
# Get the list of available test suites.
testsuites = request.get_db().testsuite.values()
# Gather the list of all run orders and all machines.
def to_key(name):
first = name.split('.', 1)[0]
if first.isdigit():
return (int(first), name)
return (first, name)
all_machines = set()
all_orders = set()
for ts in testsuites:
for name, in ts.query(ts.Machine.name):
all_machines.add(name)
for name, in ts.query(ts.Order.llvm_project_revision):
all_orders.add(name)
all_machines = sorted(all_machines)
all_orders = sorted(all_orders, key=to_key)
return render_template("v4_summary_report_ui.html",
config=config, all_machines=all_machines,
all_orders=all_orders)
@db_route("/summary_report", only_v3=False)
def v4_summary_report():
# Load the summary report configuration.
config_path = get_summary_config_path()
if not os.path.exists(config_path):
return render_template("error.html", message="""\
You must define a summary report configuration first.""")
with open(config_path) as f:
config = flask.json.load(f)
# Create the report object.
report = lnt.server.reporting.summaryreport.SummaryReport(
request.get_db(), config['orders'], config['machine_names'],
config['machine_patterns'])
# Build the report.
report.build()
return render_template("v4_summary_report.html", report=report)