def index_plot_data_cache(summary_form):
key = summary_form.caching_key()
cached = flask_cache.get(key)
if cached is not None:
return cached
reports = []
hist_table, hist_field = get_history_target(
summary_form.resolution.data)
component_ids = component_names_to_ids(summary_form.component_names.data)
(since_date, to_date) = summary_form.daterange.data
if summary_form.opsysreleases.data:
opsysreleases = summary_form.opsysreleases.data
else:
opsysreleases = (
db.session.query(OpSysRelease)
.filter(OpSysRelease.status != "EOL")
.order_by(OpSysRelease.releasedate)
.all())
for osr in opsysreleases:
counts = (
db.session.query(hist_field.label("time"),
func.sum(hist_table.count).label("count"))
.group_by(hist_field)
.order_by(hist_field))
counts = counts.filter(hist_table.opsysrelease_id == osr.id)
if component_ids:
counts = (counts.join(Report)
.filter(Report.component_id.in_(component_ids)))
counts = (counts.filter(hist_field >= since_date)
.filter(hist_field <= to_date))
counts = counts.all()
dates = set(date_iterator(since_date,
summary_form.resolution.data,
to_date))
for time, count in counts:
dates.remove(time)
for date in dates:
counts.append((date, 0))
counts = sorted(counts, key=itemgetter(0))
reports.append((str(osr), counts))
cached = render_template("summary/index_plot_data.html",
reports=reports,
resolution=summary_form.resolution.data[0])
flask_cache.set(key, cached, timeout=60*60)
return cached
def index():
summary_form = SummaryForm(request.args)
summary_form.components.choices = component_list()
reports = []
if summary_form.validate():
hist_table, hist_field = get_history_target(
summary_form.resolution.data)
component_ids = []
for comp in summary_form.components.data or []:
component_ids += map(int, comp.split(','))
(since_date, to_date) = summary_form.daterange.data
if summary_form.opsysreleases.data:
opsysreleases = summary_form.opsysreleases.data
else:
opsysreleases = (
db.session.query(OpSysRelease)
.filter(OpSysRelease.status != "EOL")
.order_by(OpSysRelease.releasedate)
.all())
for osr in opsysreleases:
counts = (
db.session.query(hist_field.label("time"),
func.sum(hist_table.count).label("count"))
.group_by(hist_field)
.order_by(hist_field))
counts = counts.filter(hist_table.opsysrelease_id == osr.id)
if component_ids:
counts = (counts.join(Report)
.filter(Report.component_id.in_(component_ids)))
counts = (counts.filter(hist_field >= since_date)
.filter(hist_field <= to_date))
counts = counts.all()
dates = set(date_iterator(since_date,
summary_form.resolution.data,
to_date))
for time, count in counts:
dates.remove(time)
for date in dates:
counts.append((date, 0))
counts = sorted(counts, key=itemgetter(0))
reports.append((str(osr), counts))
return render_template("summary/index.html",
summary_form=summary_form,
reports=reports,
resolution=summary_form.resolution.data[0])
def index_plot_data_cache(summary_form):
key = summary_form.caching_key()
cached = flask_cache.get(key)
if cached is not None:
return cached
reports = []
hist_table, hist_field = get_history_target(summary_form.resolution.data)
component_ids = component_names_to_ids(summary_form.component_names.data)
(since_date, to_date) = summary_form.daterange.data
if summary_form.opsysreleases.data:
opsysreleases = summary_form.opsysreleases.data
else:
opsysreleases = (db.session.query(OpSysRelease).filter(
OpSysRelease.status != "EOL").order_by(
OpSysRelease.opsys_id).order_by(OpSysRelease.version).all())
for osr in opsysreleases:
counts = (db.session.query(
hist_field.label("time"),
func.sum(hist_table.count).label("count")).group_by(
hist_field).order_by(hist_field))
counts = counts.filter(hist_table.opsysrelease_id == osr.id)
if component_ids:
counts = (counts.join(Report).filter(
Report.component_id.in_(component_ids)))
counts = (counts.filter(hist_field >= since_date).filter(
hist_field <= to_date))
counts = counts.all()
dates = set(
date_iterator(since_date, summary_form.resolution.data, to_date))
for time, _ in counts:
dates.remove(time)
for date in dates:
counts.append((date, 0))
counts = sorted(counts, key=itemgetter(0))
reports.append((str(osr), counts))
cached = render_template("summary/index_plot_data.html",
reports=reports,
resolution=summary_form.resolution.data[0])
flask_cache.set(key, cached, timeout=60 * 60)
return cached
def compute_totals(summary_form):
component_ids = component_names_to_ids(summary_form.component_names.data)
from_date, to_date = summary_form.daterange.data
resolution = summary_form.resolution.data
table, date_column = get_history_target(summary_form.resolution.data)
# Generate sequence of days/weeks/months in the specified range.
from_date, to_date, delta = interval_delta(from_date, to_date, resolution)
dates = (db.session.query(
func.generate_series(from_date, to_date,
delta).label('date')).subquery())
if summary_form.opsysreleases.data:
# Query only requested opsys releases.
releases = (db.session.query(OpSysRelease).filter(
OpSysRelease.id.in_([
osr.id for osr in summary_form.opsysreleases.data
])).subquery())
else:
# Query all active opsys releases.
releases = (db.session.query(OpSysRelease).filter(
OpSysRelease.status != 'EOL').subquery())
# Sum daily counts for each date in the range and each opsys release.
history = (db.session.query(
date_column.label('date'),
func.sum(table.count).label('count'),
table.opsysrelease_id).filter(from_date <= date_column).filter(
date_column <= to_date).group_by(table.opsysrelease_id,
date_column))
if component_ids:
history = history.join(Report).filter(
Report.component_id.in_(component_ids))
history = history.subquery()
q = (db.session.query(
dates.c.date,
func.coalesce(history.c.count, 0).label('count'), OpSys.name,
releases.c.version).outerjoin(
releases, dates.c.date == dates.c.date).outerjoin(
history, (history.c.date == dates.c.date) &
(history.c.opsysrelease_id == releases.c.id)).join(
OpSys, OpSys.id == releases.c.opsys_id).order_by(
OpSys.id, releases.c.version, dates.c.date))
by_opsys = dict()
groups = groupby(q.all(), lambda r: f'{r.name} {r.version}')
for osr, rows in groups:
counts = [(r.date, r.count) for r in rows]
by_opsys[osr] = counts
result = {'by_opsys': by_opsys, 'from_date': from_date, 'to_date': to_date}
return result
def get_problems(filter_form, pagination):
opsysrelease_ids = [
osr.id for osr in (filter_form.opsysreleases.data or [])
]
component_ids = component_names_to_ids(filter_form.component_names.data)
if filter_form.associate.data:
associate_id = filter_form.associate.data.id
else:
associate_id = None
arch_ids = [arch.id for arch in (filter_form.arch.data or [])]
types = filter_form.type.data or []
exclude_taintflag_ids = [
tf.id for tf in (filter_form.exclude_taintflags.data or [])
]
(since_date, to_date) = filter_form.daterange.data
date_delta = to_date - since_date
if date_delta < datetime.timedelta(days=16):
resolution = "daily"
elif date_delta < datetime.timedelta(weeks=10):
resolution = "weekly"
else:
resolution = "monthly"
hist_table, hist_field = get_history_target(resolution)
probable_fix_osr_ids = [
osr.id for osr in (filter_form.probable_fix_osrs.data or [])
]
p = query_problems(
db,
hist_table,
hist_field,
opsysrelease_ids=opsysrelease_ids,
component_ids=component_ids,
associate_id=associate_id,
arch_ids=arch_ids,
exclude_taintflag_ids=exclude_taintflag_ids,
types=types,
rank_filter_fn=lambda query:
(query.filter(hist_field >= since_date).filter(hist_field <= to_date)),
function_names=filter_form.function_names.data,
binary_names=filter_form.binary_names.data,
source_file_names=filter_form.source_file_names.data,
since_version=filter_form.since_version.data,
since_release=filter_form.since_release.data,
to_version=filter_form.to_version.data,
to_release=filter_form.to_release.data,
probable_fix_osr_ids=probable_fix_osr_ids,
bug_filter=filter_form.bug_filter.data,
limit=pagination.limit,
offset=pagination.offset,
solution=filter_form.solution)
return p
def get_problems(filter_form, pagination):
opsysrelease_ids = [
osr.id for osr in (filter_form.opsysreleases.data or [])
]
component_ids = component_names_to_ids(filter_form.component_names.data)
if filter_form.associate.data:
associate_id = filter_form.associate.data.id
else:
associate_id = None
arch_ids = [arch.id for arch in (filter_form.arch.data or [])]
types = filter_form.type.data or []
exclude_taintflag_ids = [
tf.id for tf in (filter_form.exclude_taintflags.data or [])
]
(since_date, to_date) = filter_form.daterange.data
date_delta = to_date - since_date
if date_delta < datetime.timedelta(days=16):
resolution = "daily"
elif date_delta < datetime.timedelta(weeks=10):
resolution = "weekly"
else:
resolution = "monthly"
hist_table, hist_field = get_history_target(resolution)
probable_fix_osr_ids = [
osr.id for osr in (filter_form.probable_fix_osrs.data or [])
]
p = query_problems(
db,
hist_table,
hist_field,
opsysrelease_ids=opsysrelease_ids,
component_ids=component_ids,
associate_id=associate_id,
arch_ids=arch_ids,
exclude_taintflag_ids=exclude_taintflag_ids,
types=types,
rank_filter_fn=
lambda query: (query.filter(hist_field >= since_date).filter(hist_field <= to_date)),
function_names=filter_form.function_names.data,
binary_names=filter_form.binary_names.data,
source_file_names=filter_form.source_file_names.data,
since_version=filter_form.since_version.data,
since_release=filter_form.since_release.data,
to_version=filter_form.to_version.data,
to_release=filter_form.to_release.data,
probable_fix_osr_ids=probable_fix_osr_ids,
bug_filter=filter_form.bug_filter.data,
limit=pagination.limit,
offset=pagination.offset)
return p
def by_daterange(since, to):
'''
Render date-based report statistics including reports `since` date
until `to` date.
'''
try:
if isinstance(since, str) or isinstance(since, unicode):
since = datetime.datetime.strptime(since, "%Y-%m-%d").date()
if isinstance(to, str) or isinstance(to, unicode):
to = datetime.datetime.strptime(to, "%Y-%m-%d").date()
except:
return abort(400)
since = min(since, to)
to = max(since, to)
history = 'daily'
day_count = (to - since).days
if day_count > 30:
history = 'weekly'
if day_count > 360:
history = 'monthly'
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
hist_table, hist_field = queries.get_history_target(history)
total_query = queries.get_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.get_releases(db):
release_sum = queries.get_history_sum(db,
release.opsys.name,
release.version,
history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.get_report_count_by_component(db,
release.opsys.name,
release.version,
history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({
'release': release,
'sum': release_sum,
'comps': comp_data,
'percentage': percentage,
})
data = {
'since': since,
'to': to,
'total': total,
'releases': sorted(release_data, key=lambda x: x['sum'], reverse=True),
}
if request_wants_json():
return jsonify(data)
return render_template("stats/by_date.html", **data)
def by_daterange(request, since, to,
template_name='stats/by_date.html',
extra_context={}):
'''
Render date-based report statistics including reports `since` date
until `to` date.
View accepts `template_name` to be used and `extra_context` to pass
to it.
'''
db = pyfaf.storage.getDatabase()
since = min(since, to)
to = max(since, to)
history = 'daily'
day_count = (to - since).days
if day_count > 30:
history = 'weekly'
if day_count > 360:
history = 'monthly'
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
hist_table, hist_field = queries.get_history_target(history)
total_query = queries.query_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.query_releases(db):
release_sum = queries.query_history_sum(
db, release.opsys.name, release.version, history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.query_report_count_per_component(
db, release.opsys.name, release.version, history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({
'release': release,
'sum': release_sum,
'comps': comp_data,
'percentage': percentage,
})
data = {
'since': since,
'to': to,
'total': total,
'releases': sorted(release_data, key=lambda x: x['sum'], reverse=True),
}
data.update(extra_context)
return render_to_response(template_name,
data,
context_instance=RequestContext(request))
def components(self, cmdline, db, opsys, release):
"""
Get statistics for most crashing components
"""
hist_table, hist_field = get_history_target(self.history_type)
total = get_history_sum(db, opsys, release)
comps = get_report_count_by_component(db, opsys, release)
if cmdline.last:
now = datetime.datetime.now()
since = now - datetime.timedelta(days=int(cmdline.last))
comps = comps.filter(hist_field >= since)
total = total.filter(hist_field >= since)
total_num = total.first()[0]
limit = int(cmdline.count)
limit_details = int(cmdline.detail_count)
results = []
for num, (comp, count) in enumerate(comps):
if num >= limit:
break
if comp in self.comps_filter:
continue
reports = get_report_stats_by_component(db, comp, opsys, release,
self.history_type)
if cmdline.last:
reports = reports.filter(hist_field >= since)
problem_ids = set()
attached_reports = []
for report, report_count in reports:
if len(problem_ids) >= limit_details:
break
if not report.problem:
continue
if report.problem.id in problem_ids:
continue
if report.quality < 0 and not cmdline.include_low_quality:
continue
problem_ids.add(report.problem.id)
problem_url = ""
if webfaf_installed():
problem_url = reverse("problems.item",
problem_id=report.problem.id)
attached_reports.append((problem_url, report.bugs))
results.append((comp, count, attached_reports))
if not results:
return ""
out = "Components:\n\n"
for num, (comp, count, reports) in enumerate(results):
if reports:
out += ("{0}. {1} seen {2} times ({3:.0%} of all reports)\n".
format(num + 1, comp, count, count / float(total_num)))
for problem_url, bugs in reports:
if problem_url or bugs:
out += " {0} {1}\n".format(
problem_url, ", ".join(map(str, bugs)))
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
def by_daterange(request,
since,
to,
template_name='stats/by_date.html',
extra_context={}):
'''
Render date-based report statistics including reports `since` date
until `to` date.
View accepts `template_name` to be used and `extra_context` to pass
to it.
'''
if isinstance(since, str) or isinstance(since, unicode):
since = datetime.datetime.strptime(since, "%Y-%m-%d").date()
if isinstance(to, str) or isinstance(to, unicode):
to = datetime.datetime.strptime(to, "%Y-%m-%d").date()
db = pyfaf.storage.getDatabase()
since = min(since, to)
to = max(since, to)
history = 'daily'
day_count = (to - since).days
if day_count > 30:
history = 'weekly'
if day_count > 360:
history = 'monthly'
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
hist_table, hist_field = queries.get_history_target(history)
total_query = queries.get_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.get_releases(db):
release_sum = queries.get_history_sum(db,
release.opsys.name,
release.version,
history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.get_report_count_by_component(db,
release.opsys.name,
release.version,
history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({
'release': release,
'sum': release_sum,
'comps': comp_data,
'percentage': percentage,
})
data = {
'since': since,
'to': to,
'total': total,
'releases': sorted(release_data, key=lambda x: x['sum'], reverse=True),
}
data.update(extra_context)
if "application/json" in request.META.get("HTTP_ACCEPT"):
return HttpResponse(json.dumps(data, cls=WebfafJSONEncoder),
status=200,
mimetype="application/json")
else:
return render_to_response(template_name,
data,
context_instance=RequestContext(request))
def components(self, cmdline, db, opsys, release):
"""
Get statistics for most crashing components
"""
hist_table, hist_field = get_history_target(self.history_type)
total = get_history_sum(db, opsys, release)
comps = get_report_count_by_component(db, opsys, release)
if cmdline.last:
now = datetime.datetime.now()
since = now - datetime.timedelta(days=int(cmdline.last))
comps = comps.filter(hist_field >= since)
total = total.filter(hist_field >= since)
total_num = total.first()[0]
limit = int(cmdline.count)
limit_details = int(cmdline.detail_count)
results = []
for num, (comp, count) in enumerate(comps):
if num >= limit:
break
if comp in self.comps_filter:
continue
reports = get_report_stats_by_component(db, comp, opsys,
release,
self.history_type)
if cmdline.last:
reports = reports.filter(hist_field >= since)
problem_ids = set()
attached_reports = []
for report, report_count in reports:
if len(problem_ids) >= limit_details:
break
if not report.problem:
continue
if report.problem.id in problem_ids:
continue
if report.quality < 0 and not cmdline.include_low_quality:
continue
problem_ids.add(report.problem.id)
problem_url = ""
if webfaf_installed():
problem_url = reverse("problems.item",
problem_id=report.problem.id)
attached_reports.append((problem_url, report.bugs))
results.append((comp, count, attached_reports))
if not results:
return ""
out = "Components:\n\n"
for num, (comp, count, reports) in enumerate(results):
if reports:
out += ("{0}. {1} seen {2} times ({3:.0%} of all reports)\n"
.format(num + 1, comp, count, count / float(total_num)))
for problem_url, bugs in reports:
if problem_url or bugs:
out += " {0} {1}\n".format(
problem_url, ", ".join(map(str, bugs)))
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
def by_daterange(since, to):
"""
Render date-based report statistics including reports `since` date
until `to` date.
"""
try:
if isinstance(since, str) or isinstance(since, unicode):
since = datetime.datetime.strptime(since, "%Y-%m-%d").date()
if isinstance(to, str) or isinstance(to, unicode):
to = datetime.datetime.strptime(to, "%Y-%m-%d").date()
except:
return abort(400)
since = min(since, to)
to = max(since, to)
history = "daily"
day_count = (to - since).days
if day_count > 30:
history = "weekly"
if day_count > 360:
history = "monthly"
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
hist_table, hist_field = queries.get_history_target(history)
total_query = queries.get_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.get_releases(db):
release_sum = queries.get_history_sum(db, release.opsys.name, release.version, history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.get_report_count_by_component(db, release.opsys.name, release.version, history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({"release": release, "sum": release_sum, "comps": comp_data, "percentage": percentage})
data = {
"since": since,
"to": to,
"total": total,
"releases": sorted(release_data, key=lambda x: x["sum"], reverse=True),
}
if request_wants_json():
return jsonify(data)
return render_template("stats/by_date.html", **data)
def by_daterange(request, since, to,
template_name='stats/by_date.html',
extra_context={}):
'''
Render date-based report statistics including reports `since` date
until `to` date.
View accepts `template_name` to be used and `extra_context` to pass
to it.
'''
if isinstance(since, str) or isinstance(since, unicode):
since = datetime.datetime.strptime(since, "%Y-%m-%d").date()
if isinstance(to, str) or isinstance(to, unicode):
to = datetime.datetime.strptime(to, "%Y-%m-%d").date()
db = pyfaf.storage.getDatabase()
since = min(since, to)
to = max(since, to)
history = 'daily'
day_count = (to - since).days
if day_count > 30:
history = 'weekly'
if day_count > 360:
history = 'monthly'
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
hist_table, hist_field = queries.get_history_target(history)
total_query = queries.get_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.get_releases(db):
release_sum = queries.get_history_sum(
db, release.opsys.name, release.version, history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.get_report_count_by_component(
db, release.opsys.name, release.version, history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({
'release': release,
'sum': release_sum,
'comps': comp_data,
'percentage': percentage,
})
data = {
'since': since,
'to': to,
'total': total,
'releases': sorted(release_data, key=lambda x: x['sum'], reverse=True),
}
data.update(extra_context)
if "application/json" in request.META.get("HTTP_ACCEPT"):
return HttpResponse(json.dumps(data, cls=WebfafJSONEncoder),
status=200, mimetype="application/json")
else:
return render_to_response(template_name,
data,
context_instance=RequestContext(request))
def by_daterange(since, to):
'''
Render date-based report statistics including reports `since` date
until `to` date.
'''
try:
if isinstance(since, str):
since = datetime.datetime.strptime(since, "%Y-%m-%d").date()
if isinstance(to, str):
to = datetime.datetime.strptime(to, "%Y-%m-%d").date()
except: # pylint: disable=bare-except
return abort(400)
since = min(since, to)
to = max(since, to)
history = 'daily'
day_count = (to - since).days
if day_count > 30:
history = 'weekly'
if day_count > 360:
history = 'monthly'
def date_filter(query):
return query.filter(hist_field >= since).filter(hist_field < to)
_, hist_field = queries.get_history_target(history)
total_query = queries.get_history_sum(db, history=history)
total = date_filter(total_query).one()[0]
release_data = []
for release in queries.get_releases(db):
release_sum = queries.get_history_sum(
db, release.opsys.name, release.version, history=history)
release_sum = date_filter(release_sum).one()[0]
if not release_sum:
continue
percentage = int(release_sum * 100.0 / total)
comps = queries.get_report_count_by_component(
db, release.opsys.name, release.version, history=history)
comp_data = []
for comp, count in date_filter(comps).all():
comp_percentage = int(count * 100.0 / release_sum)
comp_data.append((comp, count, comp_percentage))
release_data.append({
'release': release,
'sum': release_sum,
'comps': comp_data,
'percentage': percentage,
})
data = {
'since': since,
'to': to,
'total': total,
'releases': sorted(release_data, key=lambda x: x['sum'], reverse=True),
}
if request_wants_json():
return jsonify(data)
return render_template("stats/by_date.html", **data)