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).""")
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).""")
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)
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)
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': lnt.util.stats.safe_min,
'median': lnt.util.stats.median}.get(
aggregation_fn_name, lnt.util.stats.safe_min)
# Get the MW confidence level.
try:
confidence_lv = float(request.args.get('MW_confidence_lv'))
except (TypeError, ValueError):
confidence_lv = .05
self.confidence_lv = confidence_lv
# 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 = 0
# 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
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,
num_comparison_runs=self.num_comparison_runs,
aggregation_fn=self.aggregation_fn, confidence_lv=confidence_lv)
_, self.text_report, self.html_report, self.sri = reports
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': lnt.util.stats.safe_min,
'median': lnt.util.stats.median}.get(
aggregation_fn_name, lnt.util.stats.safe_min)
# Get the MW confidence level.
try:
confidence_lv = float(request.args.get('MW_confidence_lv'))
except (TypeError, ValueError):
confidence_lv = .05
self.confidence_lv = confidence_lv
# 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 = 0
# 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
# We're going to render this on a real webpage with CSS support, so
# override the default styles and provide bootstrap class names for
# the tables.
styles = {
'body': '', 'td': '',
'h1': 'font-size: 14pt',
'table': 'width: initial; font-size: 9pt;',
'th': 'text-align: center;'
}
classes = {
'table': 'table table-striped table-condensed table-hover'
}
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,
num_comparison_runs=self.num_comparison_runs,
aggregation_fn=self.aggregation_fn, confidence_lv=confidence_lv,
styles=styles, classes=classes)
_, self.text_report, self.html_report, self.sri = reports
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': lnt.util.stats.safe_min,
'median': lnt.util.stats.median
}.get(aggregation_fn_name, lnt.util.stats.safe_min)
# Get the MW confidence level.
try:
confidence_lv = float(request.args.get('MW_confidence_lv'))
except (TypeError, ValueError):
confidence_lv = .05
self.confidence_lv = confidence_lv
# 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 = 0
# 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
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,
num_comparison_runs=self.num_comparison_runs,
aggregation_fn=self.aggregation_fn,
confidence_lv=confidence_lv)
_, self.text_report, self.html_report, self.sri = reports
