b435ceedfc
* chore: analytics endpoint * chore: created analytics chart * chore: validation errors * chore: added a new graph in advance analytics * chore: added csv exporter * chore: updated the filtering logic for analytics * chore: opitmised the analytics endpoint * chore: updated the base function for viewsets * chore: updated the export logic * chore: added type hints * chore: added type hints
397 lines
15 KiB
Python
397 lines
15 KiB
Python
from rest_framework.response import Response
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from rest_framework import status
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from typing import Dict, List, Any
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from datetime import timedelta
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from django.db.models import QuerySet, Q, Count
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from django.http import HttpRequest
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from plane.app.views.base import BaseAPIView
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from plane.app.permissions import ROLE, allow_permission
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from plane.db.models import (
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WorkspaceMember,
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Project,
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Issue,
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Cycle,
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Module,
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IssueView,
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ProjectPage,
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)
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from plane.utils.build_chart import build_analytics_chart
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from plane.bgtasks.analytic_plot_export import export_analytics_to_csv_email
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from plane.utils.date_utils import get_analytics_filters
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class AdvanceAnalyticsBaseView(BaseAPIView):
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def initialize_workspace(self, slug: str, type: str) -> None:
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self._workspace_slug = slug
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self.filters = get_analytics_filters(
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slug=slug,
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type=type,
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user=self.request.user,
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date_filter=self.request.GET.get("date_filter", None),
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project_ids=self.request.GET.get("project_ids", None),
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)
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class AdvanceAnalyticsEndpoint(AdvanceAnalyticsBaseView):
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def get_filtered_counts(self, queryset: QuerySet) -> Dict[str, int]:
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def get_filtered_count() -> int:
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if self.filters["analytics_date_range"]:
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return queryset.filter(
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created_at__gte=self.filters["analytics_date_range"]["current"][
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"gte"
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],
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created_at__lte=self.filters["analytics_date_range"]["current"][
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"lte"
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],
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).count()
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return queryset.count()
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def get_previous_count() -> int:
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if self.filters["analytics_date_range"] and self.filters[
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"analytics_date_range"
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].get("previous"):
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return queryset.filter(
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created_at__gte=self.filters["analytics_date_range"]["previous"][
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"gte"
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],
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created_at__lte=self.filters["analytics_date_range"]["previous"][
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"lte"
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],
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).count()
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return 0
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return {
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"count": get_filtered_count(),
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"filter_count": get_previous_count(),
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}
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def get_overview_data(self) -> Dict[str, Dict[str, int]]:
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return {
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"total_users": self.get_filtered_counts(
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WorkspaceMember.objects.filter(
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workspace__slug=self._workspace_slug, is_active=True
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)
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),
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"total_admins": self.get_filtered_counts(
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WorkspaceMember.objects.filter(
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workspace__slug=self._workspace_slug,
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role=ROLE.ADMIN.value,
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is_active=True,
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)
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),
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"total_members": self.get_filtered_counts(
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WorkspaceMember.objects.filter(
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workspace__slug=self._workspace_slug,
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role=ROLE.MEMBER.value,
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is_active=True,
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)
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),
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"total_guests": self.get_filtered_counts(
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WorkspaceMember.objects.filter(
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workspace__slug=self._workspace_slug,
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role=ROLE.GUEST.value,
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is_active=True,
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)
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),
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"total_projects": self.get_filtered_counts(
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Project.objects.filter(**self.filters["project_filters"])
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),
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"total_work_items": self.get_filtered_counts(
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Issue.issue_objects.filter(**self.filters["base_filters"])
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),
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"total_cycles": self.get_filtered_counts(
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Cycle.objects.filter(**self.filters["base_filters"])
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),
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"total_intake": self.get_filtered_counts(
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Issue.objects.filter(**self.filters["base_filters"]).filter(
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issue_intake__isnull=False
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)
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),
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}
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def get_work_items_stats(self) -> Dict[str, Dict[str, int]]:
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base_queryset = Issue.objects.filter(**self.filters["base_filters"])
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return {
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"total_work_items": self.get_filtered_counts(base_queryset),
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"started_work_items": self.get_filtered_counts(
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base_queryset.filter(state__group="started")
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),
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"backlog_work_items": self.get_filtered_counts(
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base_queryset.filter(state__group="backlog")
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),
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"un_started_work_items": self.get_filtered_counts(
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base_queryset.filter(state__group="unstarted")
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),
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"completed_work_items": self.get_filtered_counts(
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base_queryset.filter(state__group="completed")
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),
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}
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@allow_permission([ROLE.ADMIN, ROLE.MEMBER], level="WORKSPACE")
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def get(self, request: HttpRequest, slug: str) -> Response:
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self.initialize_workspace(slug, type="analytics")
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tab = request.GET.get("tab", "overview")
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if tab == "overview":
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return Response(
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self.get_overview_data(),
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status=status.HTTP_200_OK,
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)
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elif tab == "work-items":
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return Response(
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self.get_work_items_stats(),
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status=status.HTTP_200_OK,
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)
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return Response({"message": "Invalid tab"}, status=status.HTTP_400_BAD_REQUEST)
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class AdvanceAnalyticsStatsEndpoint(AdvanceAnalyticsBaseView):
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def get_project_issues_stats(self) -> QuerySet:
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# Get the base queryset with workspace and project filters
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base_queryset = Issue.issue_objects.filter(**self.filters["base_filters"])
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# Apply date range filter if available
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if self.filters["chart_period_range"]:
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start_date, end_date = self.filters["chart_period_range"]
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base_queryset = base_queryset.filter(
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created_at__date__gte=start_date, created_at__date__lte=end_date
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)
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return (
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base_queryset.values("project_id", "project__name")
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.annotate(
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cancelled_work_items=Count("id", filter=Q(state__group="cancelled")),
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completed_work_items=Count("id", filter=Q(state__group="completed")),
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backlog_work_items=Count("id", filter=Q(state__group="backlog")),
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un_started_work_items=Count("id", filter=Q(state__group="unstarted")),
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started_work_items=Count("id", filter=Q(state__group="started")),
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)
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.order_by("project_id")
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)
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@allow_permission([ROLE.ADMIN, ROLE.MEMBER], level="WORKSPACE")
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def get(self, request: HttpRequest, slug: str) -> Response:
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self.initialize_workspace(slug, type="chart")
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type = request.GET.get("type", "work-items")
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if type == "work-items":
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return Response(
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self.get_project_issues_stats(),
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status=status.HTTP_200_OK,
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)
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return Response({"message": "Invalid type"}, status=status.HTTP_400_BAD_REQUEST)
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class AdvanceAnalyticsChartEndpoint(AdvanceAnalyticsBaseView):
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def project_chart(self) -> List[Dict[str, Any]]:
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# Get the base queryset with workspace and project filters
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base_queryset = Issue.issue_objects.filter(**self.filters["base_filters"])
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date_filter = {}
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# Apply date range filter if available
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if self.filters["chart_period_range"]:
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start_date, end_date = self.filters["chart_period_range"]
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date_filter = {
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"created_at__date__gte": start_date,
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"created_at__date__lte": end_date,
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}
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total_work_items = base_queryset.filter(**date_filter).count()
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total_cycles = Cycle.objects.filter(
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**self.filters["base_filters"], **date_filter
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).count()
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total_modules = Module.objects.filter(
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**self.filters["base_filters"], **date_filter
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).count()
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total_intake = Issue.objects.filter(
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issue_intake__isnull=False, **self.filters["base_filters"], **date_filter
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).count()
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total_members = WorkspaceMember.objects.filter(
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workspace__slug=self._workspace_slug, is_active=True, **date_filter
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).count()
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total_pages = ProjectPage.objects.filter(
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**self.filters["base_filters"], **date_filter
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).count()
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total_views = IssueView.objects.filter(
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**self.filters["base_filters"], **date_filter
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).count()
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data = {
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"work_items": total_work_items,
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"cycles": total_cycles,
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"modules": total_modules,
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"intake": total_intake,
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"members": total_members,
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"pages": total_pages,
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"views": total_views,
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}
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return [
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{
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"key": key,
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"name": key.replace("_", " ").title(),
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"count": value or 0,
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}
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for key, value in data.items()
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]
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def work_item_completion_chart(self) -> Dict[str, Any]:
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# Get the base queryset
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queryset = (
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Issue.issue_objects.filter(**self.filters["base_filters"])
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.select_related("workspace", "state", "parent")
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.prefetch_related(
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"assignees", "labels", "issue_module__module", "issue_cycle__cycle"
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)
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)
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# Apply date range filter if available
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if self.filters["chart_period_range"]:
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start_date, end_date = self.filters["chart_period_range"]
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queryset = queryset.filter(
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created_at__date__gte=start_date, created_at__date__lte=end_date
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)
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# Get daily stats with optimized query
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daily_stats = (
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queryset.values("created_at__date")
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.annotate(
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created_count=Count("id"),
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completed_count=Count("id", filter=Q(completed_at__isnull=False)),
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)
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.order_by("created_at__date")
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)
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# Create a dictionary of existing stats with summed counts
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stats_dict = {
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stat["created_at__date"].strftime("%Y-%m-%d"): {
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"created_count": stat["created_count"],
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"completed_count": stat["completed_count"],
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}
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for stat in daily_stats
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}
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# Generate data for all days in the range
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data = []
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current_date = start_date
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while current_date <= end_date:
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date_str = current_date.strftime("%Y-%m-%d")
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stats = stats_dict.get(date_str, {"created_count": 0, "completed_count": 0})
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data.append(
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{
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"key": date_str,
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"name": date_str,
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"count": stats["created_count"] + stats["completed_count"],
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"completed_issues": stats["completed_count"],
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"created_issues": stats["created_count"],
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}
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)
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current_date += timedelta(days=1)
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schema = {
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"completed_issues": "completed_issues",
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"created_issues": "created_issues",
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}
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return {"data": data, "schema": schema}
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@allow_permission([ROLE.ADMIN, ROLE.MEMBER], level="WORKSPACE")
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def get(self, request: HttpRequest, slug: str) -> Response:
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self.initialize_workspace(slug, type="chart")
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type = request.GET.get("type", "projects")
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group_by = request.GET.get("group_by", None)
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x_axis = request.GET.get("x_axis", "PRIORITY")
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if type == "projects":
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return Response(self.project_chart(), status=status.HTTP_200_OK)
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elif type == "custom-work-items":
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# Get the base queryset
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queryset = (
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Issue.issue_objects.filter(**self.filters["base_filters"])
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.select_related("workspace", "state", "parent")
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.prefetch_related(
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"assignees", "labels", "issue_module__module", "issue_cycle__cycle"
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)
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)
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# Apply date range filter if available
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if self.filters["chart_period_range"]:
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start_date, end_date = self.filters["chart_period_range"]
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queryset = queryset.filter(
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created_at__date__gte=start_date, created_at__date__lte=end_date
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)
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return Response(
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build_analytics_chart(queryset, x_axis, group_by),
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status=status.HTTP_200_OK,
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)
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elif type == "work-items":
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return Response(
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self.work_item_completion_chart(),
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status=status.HTTP_200_OK,
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)
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return Response({"message": "Invalid type"}, status=status.HTTP_400_BAD_REQUEST)
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class AdvanceAnalyticsExportEndpoint(AdvanceAnalyticsBaseView):
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@allow_permission([ROLE.ADMIN, ROLE.MEMBER], level="WORKSPACE")
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def post(self, request: HttpRequest, slug: str) -> Response:
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self.initialize_workspace(slug, type="chart")
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queryset = Issue.issue_objects.filter(**self.filters["base_filters"])
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# Apply date range filter if available
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if self.filters["chart_period_range"]:
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start_date, end_date = self.filters["chart_period_range"]
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queryset = queryset.filter(
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created_at__date__gte=start_date, created_at__date__lte=end_date
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)
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queryset = (
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queryset.values("project_id", "project__name")
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.annotate(
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cancelled_work_items=Count("id", filter=Q(state__group="cancelled")),
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completed_work_items=Count("id", filter=Q(state__group="completed")),
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backlog_work_items=Count("id", filter=Q(state__group="backlog")),
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un_started_work_items=Count("id", filter=Q(state__group="unstarted")),
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started_work_items=Count("id", filter=Q(state__group="started")),
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)
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.order_by("project_id")
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)
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# Convert QuerySet to list of dictionaries for serialization
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serialized_data = list(queryset)
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headers = [
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"Projects",
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"Completed Issues",
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"Backlog Issues",
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"Unstarted Issues",
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"Started Issues",
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]
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keys = [
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"project__name",
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"completed_work_items",
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"backlog_work_items",
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"un_started_work_items",
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"started_work_items",
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]
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email = request.user.email
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# Send serialized data to background task
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export_analytics_to_csv_email.delay(serialized_data, headers, keys, email, slug)
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return Response(
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{
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"message": f"Once the export is ready it will be emailed to you at {str(email)}"
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},
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status=status.HTTP_200_OK,
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)
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