dashboard.py

"""Home view."""
import datetime
from django.views.generic import TemplateView
from django.db.models import Count
from django.db.models.functions import TruncMonth
from django.db.models import Q  

from ..exploit.models import Exploit


class DashboardTemplateView(TemplateView):
    """Hometemplate view."""

    template_name = "pages/dashboard.html"

    def get_context_data(self, **kwargs):
        Color = ["progress-bar bg-success", "progress-bar bg-info text-dark", "progress-bar bg-warning text-dark", "progress-bar bg-danger" ]
        """Get context data."""
        # Call the base implementation first to get a context
        
        context = super().get_context_data(**kwargs)
        # Get a count of the total number of exploits we have into our context.
        context["exploits_count"] = Exploit.objects.all().count()
        # Get a count of how many exploit entries have been added within the last day.
        date_from = datetime.datetime.now() - datetime.timedelta(days=1)
        context["24_hours"] = Exploit.objects.filter(date_created__gte=date_from).count()
        # Get a count oh how many exploits have been added within the last 7 days.
        date_from = datetime.datetime.now() - datetime.timedelta(days=7)
        context["7_days"] = Exploit.objects.filter(date_created__gte=date_from).count()
        # For each source, get a count of its associated exploits, it percent representation, and what color to display it as.
        sources = Exploit.objects.values('source').annotate(count=Count('source')).order_by()
        color = 0
        for source in sources:
            source['percentage'] = format(source['count'] / context["exploits_count"] * 100, '.2f')
            if color > 3:
                color = 0
            source['color'] = Color[color]
            color += 1

        context["sources"] = sources
        # Begin assembling the data for the highchart.
        # Start by querying for number of monthly entries per source this year.
        data_sets = Exploit.objects.filter(Q(date_created__year=datetime.datetime.now().date().year)).values('source').annotate(month=TruncMonth('date_created')).values('month').annotate(c=Count('id')).values('month', 'c', 'source').order_by('source')
        # Get a list of the sources.
        options = Exploit.objects.order_by().values('source').distinct()
        print(data_sets)
        # Set a list of 0s sized by current month digit. This will hold the per month count.
        data_set =  [0] * (datetime.datetime.now().month)
        graph_data = []
        # Get number of monthly entries with respect to source in a graphable format.
        for option in options:
            for data in data_sets:
                if data['source'] == option['source']:
                    if data['month'] is not None:
                        data_set[data['month'].month-1] = data['c']
            # Append the source with its monthly counts to graph_data.
            graph_data.append({"name": option['source'], "data": data_set})
            # Reset the monthly counts to 0.
            data_set =  [0] * (datetime.datetime.now().month )

        # oldest_date = Exploit.objects.order_by('date_published').values('date_published').first()
        current_date = datetime.datetime.now()
        # year = oldest_date['date_published'].year
        # Save year info to context for highchart
        context["years"] = [2022, 2023]
        context["year"] = current_date.year
        # Set the generated graph data into context.
        context["data"] = graph_data

        # Add failure to download count to context
        context["download_failures"] = Exploit.objects.filter(Q(download_failed=True, ignore=False, fixed=False)).count()
        # Return our built context to be used by the template.
        return context