def route_vendor(timespan_days=30):
""" A analytics screen to show information about users """
# get data for this time period
cnt_total = {}
cached_cnt = {}
yesterday = datetime.date.today() - datetime.timedelta(days=1)
datestr_start = _get_datestr_from_datetime(yesterday - datetime.timedelta(days=timespan_days))
datestr_end = _get_datestr_from_datetime(yesterday)
for ug in db.session.query(AnalyticVendor).\
filter(and_(AnalyticVendor.datestr > datestr_start,
AnalyticVendor.datestr <= datestr_end)):
display_name = ug.vendor.display_name
key = str(ug.datestr) + display_name
if key not in cached_cnt:
cached_cnt[key] = ug.cnt
if not display_name in cnt_total:
cnt_total[display_name] = ug.cnt
continue
cnt_total[display_name] += ug.cnt
# find most popular user agent strings
most_popular = []
for key, value in sorted(iter(cnt_total.items()), key=lambda k_v: (k_v[1], k_v[0]), reverse=True):
most_popular.append(key)
if len(most_popular) >= 6:
break
# generate enough for the template
datasets = []
palette = [
'ef4760', # red
'ffd160', # yellow
'06c990', # green
'2f8ba0', # teal
'845f80', # purple
'ee8510', # orange
]
idx = 0
for value in most_popular:
dataset = {}
dataset['label'] = value
dataset['color'] = palette[idx % 6]
idx += 1
data = []
for i in range(timespan_days):
datestr = _get_datestr_from_datetime(yesterday - datetime.timedelta(days=i))
key = str(datestr) + value
dataval = 'NaN'
if key in cached_cnt:
dataval = str(cached_cnt[key])
data.append(dataval)
dataset['data'] = '[' + ', '.join(data[::-1]) + ']'
datasets.append(dataset)
return render_template('analytics-vendor.html',
category='analytics',
labels_user_agent=_get_chart_labels_days(timespan_days)[::-1],
datasets=datasets)
def route_show(firmware_id):
""" Show firmware information """
# get details about the firmware
fw = db.session.query(Firmware).\
filter(Firmware.firmware_id == firmware_id).\
first()
if not fw:
flash('No firmware matched!', 'danger')
return redirect(url_for('firmware.route_firmware'))
# security check
if not fw.check_acl('@view'):
flash('Permission denied: Insufficient permissions to view firmware',
'danger')
return redirect(url_for('firmware.route_firmware'))
# get data for the last month or year
graph_data = []
graph_labels = None
if fw.check_acl('@view-analytics') and not fw.do_not_track:
if fw.timestamp.replace(
tzinfo=None) > datetime.datetime.today() - datetime.timedelta(
days=30):
datestr = _get_datestr_from_datetime(datetime.date.today() -
datetime.timedelta(days=31))
data = db.session.query(AnalyticFirmware.cnt).\
filter(AnalyticFirmware.firmware_id == fw.firmware_id).\
filter(AnalyticFirmware.datestr > datestr).\
order_by(AnalyticFirmware.datestr.desc()).all()
graph_data = [r[0] for r in data]
graph_data = graph_data[::-1]
graph_labels = _get_chart_labels_days(limit=len(data))[::-1]
else:
datestr = _get_datestr_from_datetime(datetime.date.today() -
datetime.timedelta(days=360))
data = db.session.query(AnalyticFirmware.cnt).\
filter(AnalyticFirmware.firmware_id == fw.firmware_id).\
filter(AnalyticFirmware.datestr > datestr).\
order_by(AnalyticFirmware.datestr.desc()).all()
# put in month-sized buckets
for _ in range(12):
graph_data.append(0)
cnt = 0
for res in data:
graph_data[int(cnt / 30)] += res[0]
cnt += 1
graph_data = graph_data[::-1]
graph_labels = _get_chart_labels_months()[::-1]
return render_template('firmware-details.html',
category='firmware',
fw=fw,
graph_data=graph_data,
graph_labels=graph_labels)
def route_dashboard():
user = db.session.query(User).filter(
User.username == '*****@*****.**').first()
settings = _get_settings()
default_admin_password = False
if user and user.verify_password('Pa$$w0rd'):
default_admin_password = True
# get the 10 most recent firmwares
fws = db.session.query(Firmware).\
filter(Firmware.user_id == g.user.user_id).\
join(Remote).filter(Remote.name != 'deleted').\
order_by(Firmware.timestamp.desc()).limit(10).all()
download_cnt = 0
devices_cnt = 0
appstream_ids = {}
for fw in g.user.vendor.fws:
download_cnt += fw.download_cnt
for md in fw.mds:
appstream_ids[md.appstream_id] = fw
devices_cnt = len(appstream_ids)
# this is somewhat klunky
data = []
datestr = _get_datestr_from_datetime(datetime.date.today() -
datetime.timedelta(days=31))
for cnt in db.session.query(AnalyticVendor.cnt).\
filter(AnalyticVendor.vendor_id == g.user.vendor.vendor_id).\
filter(AnalyticVendor.datestr > datestr).\
order_by(AnalyticVendor.datestr):
data.append(int(cnt[0]))
return render_template(
'dashboard.html',
fws_recent=fws,
devices_cnt=devices_cnt,
download_cnt=download_cnt,
labels_days=_get_chart_labels_days(limit=len(data))[::-1],
data_days=data,
server_warning=settings.get('server_warning', None),
category='home',
default_admin_password=default_admin_password)
def route_month():
""" A analytics screen to show information about users """
# this is somewhat klunky
data = []
now = datetime.date.today() - datetime.timedelta(days=1)
for _ in range(30):
datestr = _get_datestr_from_datetime(now)
analytic = db.session.query(Analytic).\
filter(Analytic.datestr == datestr).\
first()
if analytic:
data.append(int(analytic.cnt))
else:
data.append(0)
# back one day
now -= datetime.timedelta(days=1)
return render_template('analytics-month.html',
category='analytics',
labels_days=_get_chart_labels_days()[::-1],
data_days=data[::-1])
def route_vendor(timespan_days=30, vendor_cnt=6, smoothing=0):
""" A analytics screen to show information about users """
# get data for this time period
cnt_total = defaultdict(int)
cached_cnt = defaultdict(int)
yesterday = datetime.date.today() - datetime.timedelta(days=1)
datestr_start = _get_datestr_from_datetime(yesterday - datetime.timedelta(
days=timespan_days))
datestr_end = _get_datestr_from_datetime(yesterday)
print('get data for', datestr_start, datestr_end)
for ug in db.session.query(AnalyticVendor)\
.filter(and_(AnalyticVendor.datestr >= datestr_start,
AnalyticVendor.datestr <= datestr_end)):
display_name = ug.vendor.display_name
key = str(ug.datestr) + display_name
cached_cnt[key] += ug.cnt
cnt_total[display_name] += ug.cnt
# find most popular user agent strings
most_popular = []
for key, value in sorted(iter(cnt_total.items()),
key=lambda k_v: (k_v[1], k_v[0]),
reverse=True):
most_popular.append(key)
if len(most_popular) >= vendor_cnt:
break
# optionally smooth
if not smoothing:
smoothing = int(timespan_days / 25)
# generate enough for the template
datasets = []
palette = [
'ef4760', # red
'ffd160', # yellow
'06c990', # green
'2f8ba0', # teal
'845f80', # purple
'ee8510', # orange
]
idx = 0
for value in sorted(most_popular):
dataset = {}
dataset['label'] = value
dataset['color'] = palette[idx % 6]
idx += 1
data = []
for i in range(timespan_days, 0, -1):
datestr = _get_datestr_from_datetime(yesterday -
datetime.timedelta(days=i))
key = str(datestr) + value
dataval = 0
if key in cached_cnt:
dataval = cached_cnt[key]
data.append(dataval)
if smoothing > 1:
data = _running_mean(data, smoothing)
dataset['data'] = json.dumps(data)
datasets.append(dataset)
return render_template(
'analytics-vendor.html',
category='analytics',
labels_user_agent=_get_chart_labels_days(timespan_days)[::-1],
datasets=datasets)
def route_reportattrs_kind(kind, timespan_days=90):
""" A analytics screen to show information about users """
# get data for this time period
cnt_total = {}
yesterday = datetime.date.today() - datetime.timedelta(days=1)
datestr_start = yesterday - datetime.timedelta(days=timespan_days)
cnt_total = {}
cached_cnt = {}
for report_ts, attr_val in db.session.query(Report.timestamp,
ReportAttribute.value)\
.filter(ReportAttribute.key == kind)\
.join(Report)\
.filter(and_(Report.timestamp > datestr_start,
Report.timestamp <= yesterday)):
key = str(_get_datestr_from_datetime(report_ts)) + attr_val
if key not in cached_cnt:
cached_cnt[key] = 1
else:
cached_cnt[key] += 1
if not attr_val in cnt_total:
cnt_total[attr_val] = 1
continue
cnt_total[attr_val] += 1
# find most popular user agent strings
most_popular = []
for key, value in sorted(iter(cnt_total.items()),
key=lambda k_v: (k_v[1], k_v[0]),
reverse=True):
most_popular.append(key)
if len(most_popular) >= 6:
break
# generate enough for the template
datasets = []
palette = [
'ef4760', # red
'ffd160', # yellow
'06c990', # green
'2f8ba0', # teal
'845f80', # purple
'ee8510', # orange
]
idx = 0
for value in most_popular:
dataset = {}
dataset['label'] = value
dataset['color'] = palette[idx % 6]
idx += 1
data = []
for i in range(timespan_days):
datestr = _get_datestr_from_datetime(yesterday -
datetime.timedelta(days=i))
key = str(datestr) + value
dataval = 'NaN'
if key in cached_cnt:
dataval = str(cached_cnt[key])
data.append(dataval)
dataset['data'] = '[' + ', '.join(data[::-1]) + ']'
datasets.append(dataset)
return render_template(
'analytics-reportattrs-kind.html',
category='analytics',
kind=kind,
labels_user_agent=_get_chart_labels_days(timespan_days)[::-1],
datasets=datasets)
def route_user_agents(kind='APP', timespan_days=30):
""" A analytics screen to show information about users """
# map back to UseragentKind
try:
kind_enum = UseragentKind[kind]
except KeyError as e:
flash('Unable to view analytic type: {}'.format(str(e)), 'danger')
return redirect(url_for('analytics.route_user_agents'))
# get data for this time period
cnt_total = {}
cached_cnt = {}
yesterday = datetime.date.today() - datetime.timedelta(days=1)
datestr_start = _get_datestr_from_datetime(yesterday - datetime.timedelta(
days=timespan_days))
datestr_end = _get_datestr_from_datetime(yesterday)
for ug in db.session.query(Useragent).\
filter(Useragent.kind == kind_enum.value).\
filter(and_(Useragent.datestr > datestr_start,
Useragent.datestr <= datestr_end)):
user_agent_safe = _user_agent_wildcard(ug.value)
if kind == 'FWUPD':
splt = user_agent_safe.split('.', 3)
if len(splt) == 3:
user_agent_safe = '{}.{}.x'.format(splt[0], splt[1])
key = str(ug.datestr) + user_agent_safe
if key not in cached_cnt:
cached_cnt[key] = ug.cnt
else:
cached_cnt[key] += ug.cnt
if not user_agent_safe in cnt_total:
cnt_total[user_agent_safe] = ug.cnt
continue
cnt_total[user_agent_safe] += ug.cnt
# find most popular user agent strings
most_popular = []
for key, value in sorted(iter(cnt_total.items()),
key=lambda k_v: (k_v[1], k_v[0]),
reverse=True):
most_popular.append(key)
if len(most_popular) >= 6:
break
# generate enough for the template
datasets = []
palette = [
'ef4760', # red
'ffd160', # yellow
'06c990', # green
'2f8ba0', # teal
'845f80', # purple
'ee8510', # orange
]
idx = 0
for value in most_popular:
dataset = {}
dataset['label'] = value
dataset['color'] = palette[idx % 6]
idx += 1
data = []
for i in range(timespan_days):
datestr = _get_datestr_from_datetime(yesterday -
datetime.timedelta(days=i))
key = str(datestr) + value
dataval = 'NaN'
if key in cached_cnt:
dataval = str(cached_cnt[key])
data.append(dataval)
dataset['data'] = '[' + ', '.join(data[::-1]) + ']'
datasets.append(dataset)
return render_template(
'analytics-user-agent.html',
category='analytics',
kind=kind,
labels_user_agent=_get_chart_labels_days(timespan_days)[::-1],
datasets=datasets)
