def product_type_counts(request):
form = ProductTypeCountsForm()
opened_in_period_list = []
oip = None
cip = None
aip = None
all_current_in_pt = None
top_ten = None
pt = None
today = timezone.now()
first_of_month = today.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
mid_month = first_of_month.replace(day=15, hour=23, minute=59, second=59, microsecond=999999)
end_of_month = mid_month.replace(day=monthrange(today.year, today.month)[1], hour=23, minute=59, second=59,
microsecond=999999)
start_date = first_of_month
end_date = end_of_month
if request.method == 'GET' and 'month' in request.GET and 'year' in request.GET and 'product_type' in request.GET:
form = ProductTypeCountsForm(request.GET)
if form.is_valid():
pt = form.cleaned_data['product_type']
month = int(form.cleaned_data['month'])
year = int(form.cleaned_data['year'])
first_of_month = first_of_month.replace(month=month, year=year)
month_requested = datetime(year, month, 1)
end_of_month = month_requested.replace(day=monthrange(month_requested.year, month_requested.month)[1],
hour=23, minute=59, second=59, microsecond=999999)
start_date = first_of_month
start_date = datetime(start_date.year,
start_date.month, start_date.day,
tzinfo=timezone.get_current_timezone())
end_date = end_of_month
end_date = datetime(end_date.year,
end_date.month, end_date.day,
tzinfo=timezone.get_current_timezone())
oip = opened_in_period(start_date, end_date, pt)
# trending data - 12 months
for x in range(12, 0, -1):
opened_in_period_list.append(
opened_in_period(start_date + relativedelta(months=-x), end_of_month + relativedelta(months=-x),
pt))
opened_in_period_list.append(oip)
closed_in_period = Finding.objects.filter(mitigated__range=[start_date, end_date],
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium', 'Low')).values(
'numerical_severity').annotate(Count('numerical_severity')).order_by('numerical_severity')
total_closed_in_period = Finding.objects.filter(mitigated__range=[start_date, end_date],
test__engagement__product__prod_type=pt,
severity__in=(
'Critical', 'High', 'Medium', 'Low')).aggregate(
total=Sum(
Case(When(severity__in=('Critical', 'High', 'Medium', 'Low'),
then=Value(1)),
output_field=IntegerField())))['total']
overall_in_pt = Finding.objects.filter(date__lt=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium', 'Low')).values(
'numerical_severity').annotate(Count('numerical_severity')).order_by('numerical_severity')
total_overall_in_pt = Finding.objects.filter(date__lte=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium', 'Low')).aggregate(
total=Sum(
Case(When(severity__in=('Critical', 'High', 'Medium', 'Low'),
then=Value(1)),
output_field=IntegerField())))['total']
all_current_in_pt = Finding.objects.filter(date__lte=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=(
'Critical', 'High', 'Medium', 'Low')).prefetch_related(
'test__engagement__product',
'test__engagement__product__prod_type',
'test__engagement__risk_acceptance',
'reporter').order_by(
'numerical_severity')
top_ten = Product.objects.filter(engagement__test__finding__date__lte=end_date,
engagement__test__finding__verified=True,
engagement__test__finding__false_p=False,
engagement__test__finding__duplicate=False,
engagement__test__finding__out_of_scope=False,
engagement__test__finding__mitigated__isnull=True,
engagement__test__finding__severity__in=(
'Critical', 'High', 'Medium', 'Low'),
prod_type=pt).annotate(
critical=Sum(
Case(When(engagement__test__finding__severity='Critical', then=Value(1)),
output_field=IntegerField())
),
high=Sum(
Case(When(engagement__test__finding__severity='High', then=Value(1)),
output_field=IntegerField())
),
medium=Sum(
Case(When(engagement__test__finding__severity='Medium', then=Value(1)),
output_field=IntegerField())
),
low=Sum(
Case(When(engagement__test__finding__severity='Low', then=Value(1)),
output_field=IntegerField())
),
total=Sum(
Case(When(engagement__test__finding__severity__in=(
'Critical', 'High', 'Medium', 'Low'), then=Value(1)),
output_field=IntegerField()))
).order_by('-critical', '-high', '-medium', '-low')[:10]
cip = {'S0': 0,
'S1': 0,
'S2': 0,
'S3': 0,
'Total': total_closed_in_period}
aip = {'S0': 0,
'S1': 0,
'S2': 0,
'S3': 0,
'Total': total_overall_in_pt}
for o in closed_in_period:
cip[o['numerical_severity']] = o['numerical_severity__count']
for o in overall_in_pt:
aip[o['numerical_severity']] = o['numerical_severity__count']
else:
messages.add_message(request, messages.ERROR, "Please choose month and year and the Product Type.",
extra_tags='alert-danger')
add_breadcrumb(title="Bi-Weekly Metrics", top_level=True, request=request)
return render(request,
'dojo/pt_counts.html',
{'form': form,
'start_date': start_date,
'end_date': end_date,
'opened_in_period': oip,
'trending_opened': opened_in_period_list,
'closed_in_period': cip,
'overall_in_pt': aip,
'all_current_in_pt': all_current_in_pt,
'top_ten': top_ten,
'pt': pt}
)
def product_type_counts(request):
form = ProductTypeCountsForm()
opened_in_period_list = []
oip = None
cip = None
aip = None
all_current_in_pt = None
top_ten = None
pt = None
today = timezone.now()
first_of_month = today.replace(day=1,
hour=0,
minute=0,
second=0,
microsecond=0)
mid_month = first_of_month.replace(day=15,
hour=23,
minute=59,
second=59,
microsecond=999999)
end_of_month = mid_month.replace(day=monthrange(today.year,
today.month)[1],
hour=23,
minute=59,
second=59,
microsecond=999999)
start_date = first_of_month
end_date = end_of_month
if request.method == 'GET' and 'month' in request.GET and 'year' in request.GET and 'product_type' in request.GET:
form = ProductTypeCountsForm(request.GET)
if form.is_valid():
pt = form.cleaned_data['product_type']
month = int(form.cleaned_data['month'])
year = int(form.cleaned_data['year'])
first_of_month = first_of_month.replace(month=month, year=year)
month_requested = datetime(year, month, 1)
end_of_month = month_requested.replace(day=monthrange(
month_requested.year, month_requested.month)[1],
hour=23,
minute=59,
second=59,
microsecond=999999)
start_date = first_of_month
start_date = datetime(start_date.year,
start_date.month,
start_date.day,
tzinfo=timezone.get_current_timezone())
end_date = end_of_month
end_date = datetime(end_date.year,
end_date.month,
end_date.day,
tzinfo=timezone.get_current_timezone())
oip = opened_in_period(start_date, end_date, pt)
# trending data - 12 months
for x in range(12, 0, -1):
opened_in_period_list.append(
opened_in_period(start_date + relativedelta(months=-x),
end_of_month + relativedelta(months=-x),
pt))
opened_in_period_list.append(oip)
closed_in_period = Finding.objects.filter(
mitigated__range=[start_date, end_date],
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium',
'Low')).values('numerical_severity').annotate(
Count('numerical_severity')).order_by(
'numerical_severity')
total_closed_in_period = Finding.objects.filter(
mitigated__range=[start_date, end_date],
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium',
'Low')).aggregate(total=Sum(
Case(When(severity__in=('Critical', 'High',
'Medium', 'Low'),
then=Value(1)),
output_field=IntegerField())))['total']
overall_in_pt = Finding.objects.filter(
date__lt=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium',
'Low')).values('numerical_severity').annotate(
Count('numerical_severity')).order_by(
'numerical_severity')
total_overall_in_pt = Finding.objects.filter(
date__lte=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium',
'Low')).aggregate(total=Sum(
Case(When(severity__in=('Critical', 'High',
'Medium', 'Low'),
then=Value(1)),
output_field=IntegerField())))['total']
all_current_in_pt = Finding.objects.filter(
date__lte=end_date,
verified=True,
false_p=False,
duplicate=False,
out_of_scope=False,
mitigated__isnull=True,
test__engagement__product__prod_type=pt,
severity__in=('Critical', 'High', 'Medium',
'Low')).prefetch_related(
'test__engagement__product',
'test__engagement__product__prod_type',
'test__engagement__risk_acceptance',
'reporter').order_by('numerical_severity')
top_ten = Product.objects.filter(
engagement__test__finding__date__lte=end_date,
engagement__test__finding__verified=True,
engagement__test__finding__false_p=False,
engagement__test__finding__duplicate=False,
engagement__test__finding__out_of_scope=False,
engagement__test__finding__mitigated__isnull=True,
engagement__test__finding__severity__in=('Critical', 'High',
'Medium', 'Low'),
prod_type=pt).annotate(
critical=Sum(
Case(When(
engagement__test__finding__severity='Critical',
then=Value(1)),
output_field=IntegerField())),
high=Sum(
Case(When(engagement__test__finding__severity='High',
then=Value(1)),
output_field=IntegerField())),
medium=Sum(
Case(When(engagement__test__finding__severity='Medium',
then=Value(1)),
output_field=IntegerField())),
low=Sum(
Case(When(engagement__test__finding__severity='Low',
then=Value(1)),
output_field=IntegerField())),
total=Sum(
Case(When(engagement__test__finding__severity__in=(
'Critical', 'High', 'Medium', 'Low'),
then=Value(1)),
output_field=IntegerField()))).order_by(
'-critical', '-high', '-medium', '-low')[:10]
cip = {
'S0': 0,
'S1': 0,
'S2': 0,
'S3': 0,
'Total': total_closed_in_period
}
aip = {
'S0': 0,
'S1': 0,
'S2': 0,
'S3': 0,
'Total': total_overall_in_pt
}
for o in closed_in_period:
cip[o['numerical_severity']] = o['numerical_severity__count']
for o in overall_in_pt:
aip[o['numerical_severity']] = o['numerical_severity__count']
else:
messages.add_message(
request,
messages.ERROR,
"Please choose month and year and the Product Type.",
extra_tags='alert-danger')
add_breadcrumb(title="Bi-Weekly Metrics", top_level=True, request=request)
return render(
request, 'dojo/pt_counts.html', {
'form': form,
'start_date': start_date,
'end_date': end_date,
'opened_in_period': oip,
'trending_opened': opened_in_period_list,
'closed_in_period': cip,
'overall_in_pt': aip,
'all_current_in_pt': all_current_in_pt,
'top_ten': top_ten,
'pt': pt
})
