def _trends_render_with_graph(self, collection, num, num_days):
"""
Render trend data with UTF8 graphs
"""
row = "{component:<40} {jump:>7} {graph:>" + str(num_days) + "}"
txt = row.format(component="Component", jump="Jump", graph="Graph")
out = txt + "\n"
out += "-" * len(txt) + "\n"
for comp in collection[:num]:
counts = []
for day in prev_days(num_days):
counts.append(comp.history[day])
minval = min(counts)
maxval = max(counts)
scale = ((maxval - minval) << 8) // (len(self.graph_symbols) - 1)
scale = max(scale, 1)
graph = ""
for day in prev_days(num_days):
graph += self.graph_symbols[(
(comp.history[day] - minval) << 8) // scale]
out += row.format(component=comp.name,
jump=comp.jump,
a=comp.a,
b=comp.b,
graph=graph.replace(" ", "") + "\n\n")
return out
def _trends_render_with_graph(self, collection, num, num_days):
"""
Render trend data with UTF8 graphs
"""
row = "{component:<40} {jump:>7} {graph:>" + str(num_days) + "}"
txt = row.format(component="Component", jump="Jump", graph="Graph")
out = txt + "\n"
out += "-" * len(txt) + "\n"
for comp in collection[:num]:
counts = []
for day in prev_days(num_days):
counts.append(comp.history[day])
minval = min(counts)
maxval = max(counts)
scale = ((maxval - minval) << 8) // (len(self.graph_symbols) - 1)
scale = max(scale, 1)
graph = ""
for day in prev_days(num_days):
graph += self.graph_symbols[((comp.history[day] - minval)
<< 8) // scale]
out += row.format(component=comp.name,
jump=comp.jump,
a=comp.a,
b=comp.b,
graph=graph.replace(" ", "") + "\n\n")
return out
def make_up_history(self, report, over_days):
"""
Make up history counts for report for `over_days` days.
"""
total = 0
daily = []
weekly = []
monthly = []
self.db.session.delete(report.history_daily[0])
self.db.session.delete(report.history_weekly[0])
self.db.session.delete(report.history_monthly[0])
opsysrelease = report.opsysreleases[0].opsysrelease
for i, day in enumerate(prev_days(over_days)):
d = ReportHistoryDaily(report=report,
opsysrelease=opsysrelease,
count=i,
day=day)
w = ReportHistoryWeekly(report=report,
opsysrelease=opsysrelease,
count=i,
week=day)
m = ReportHistoryMonthly(report=report,
opsysrelease=opsysrelease,
count=i,
month=day)
total += i
daily.append(d)
weekly.append(w)
monthly.append(m)
report.history_daily = daily
report.history_weekly = weekly
report.history_monthly = monthly
report.first_occurrence = daily[0].day
report.last_occurrence = daily[-1].day
return total
def make_up_history(self, report, over_days):
"""
Make up history counts for report for `over_days` days.
"""
total = 0
daily = []
weekly = []
monthly = []
self.db.session.delete(report.history_daily[0])
self.db.session.delete(report.history_weekly[0])
self.db.session.delete(report.history_monthly[0])
opsysrelease = report.opsysreleases[0].opsysrelease
for i, day in enumerate(prev_days(over_days)):
d = ReportHistoryDaily(report=report,
opsysrelease=opsysrelease,
count=i,
day=day)
w = ReportHistoryWeekly(report=report,
opsysrelease=opsysrelease,
count=i,
week=day)
m = ReportHistoryMonthly(report=report,
opsysrelease=opsysrelease,
count=i,
month=day)
total += i
daily.append(d)
weekly.append(w)
monthly.append(m)
report.history_daily = daily
report.history_weekly = weekly
report.history_monthly = monthly
report.first_occurrence = daily[0].day
report.last_occurrence = daily[-1].day
return total
def trends(self, cmdline, db, opsys, release):
"""
Get trends for crashing components
"""
hist_table, hist_field = get_history_target(self.history_type)
num_days = 7
if cmdline.last:
num_days = int(cmdline.last)
last_date = datetime.date.today() - datetime.timedelta(days=num_days)
comp_detail = []
comps = get_report_count_by_component(db, opsys, release)
comps = comps.filter(hist_field >= last_date)
for (comp, count) in comps:
if comp.name in self.comps_filter:
continue
report_ids = (db.session.query(
Report.id).join(OpSysComponent).filter(
OpSysComponent.id == comp.id)).subquery()
history = (db.session.query(
hist_field,
func.sum(hist_table.count).label("count")).filter(
hist_table.report_id.in_(report_ids)).filter(
hist_field >= last_date).filter(
hist_field < datetime.date.today()).group_by(
hist_field).order_by(hist_field).all())
if len(history) < 2:
continue
hist_dict = collections.defaultdict(int)
for key, value in history:
hist_dict[key] = value
# Compute linear regression
xsum, ysum, xysum, xxsum, yysum = 0., 0., 0., 0., 0.
for x, day in enumerate(prev_days(num_days)):
y = hist_dict[day]
xsum += x
ysum += y
xysum += x * y
xxsum += x * x
yysum += y * y
# y = bx + a
b = xysum - xsum * ysum // num_days
b //= xxsum - xsum**2 // num_days
a = ysum - b * xsum
a //= num_days
first_day = hist_dict[prev_days(num_days)[0]]
last_day = hist_dict[prev_days(num_days)[-1]]
Comp = collections.namedtuple("Component", "name jump a b history")
comp_tuple = Comp(name=comp.name,
jump=last_day - first_day,
a=a,
b=b,
history=hist_dict)
comp_detail.append(comp_tuple)
trend_data = sorted(comp_detail, key=lambda x: x.b, reverse=True)
if not trend_data:
return ""
# render trend data
render_fn = self._trends_render
if cmdline.graph:
render_fn = self._trends_render_with_graph
out = "Most destabilized components:\n\n"
out += render_fn(trend_data, cmdline.count, num_days)
out += "\n"
out += "Most stabilized components:\n\n"
trend_data.reverse()
out += render_fn(trend_data, cmdline.count, num_days)
out += "\n"
return out
def trends(self, cmdline, db, opsys, release):
"""
Get trends for crashing components
"""
hist_table, hist_field = get_history_target(self.history_type)
num_days = 7
if cmdline.last:
num_days = int(cmdline.last)
last_date = datetime.date.today() - datetime.timedelta(days=num_days)
comp_detail = []
comps = get_report_count_by_component(db, opsys, release)
comps = comps.filter(hist_field >= last_date)
for (comp, count) in comps:
if comp.name in self.comps_filter:
continue
report_ids = (db.session.query(Report.id)
.join(OpSysComponent)
.filter(OpSysComponent.id == comp.id)).subquery()
history = (db.session.query(hist_field,
func.sum(hist_table.count)
.label("count"))
.filter(hist_table.report_id.in_(report_ids))
.filter(hist_field >= last_date)
.filter(hist_field < datetime.date.today())
.group_by(hist_field)
.order_by(hist_field).all())
if len(history) < 2:
continue
hist_dict = collections.defaultdict(int)
for key, value in history:
hist_dict[key] = value
# Compute linear regression
xsum, ysum, xysum, xxsum, yysum = 0., 0., 0., 0., 0.
for x, day in enumerate(prev_days(num_days)):
y = hist_dict[day]
xsum += x
ysum += y
xysum += x * y
xxsum += x * x
yysum += y * y
# y = bx + a
b = xysum - xsum * ysum // num_days
b //= xxsum - xsum ** 2 // num_days
a = ysum - b * xsum
a //= num_days
first_day = hist_dict[prev_days(num_days)[0]]
last_day = hist_dict[prev_days(num_days)[-1]]
Comp = collections.namedtuple("Component", "name jump a b history")
comp_tuple = Comp(
name=comp.name,
jump=last_day - first_day,
a=a,
b=b,
history=hist_dict)
comp_detail.append(comp_tuple)
trend_data = sorted(comp_detail, key=lambda x: x.b, reverse=True)
if not trend_data:
return ""
# render trend data
render_fn = self._trends_render
if cmdline.graph:
render_fn = self._trends_render_with_graph
out = "Most destabilized components:\n\n"
out += render_fn(trend_data, cmdline.count, num_days)
out += "\n"
out += "Most stabilized components:\n\n"
trend_data.reverse()
out += render_fn(trend_data, cmdline.count, num_days)
out += "\n"
return out
