feat: add projects analytics endpoint
This commit is contained in:
ivannoskov
@@ -491,7 +491,14 @@ class Postgres(DatabaseBase, Database):
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return (
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await query.prefetch_related(
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'project', 'project__channel', 'purchase_channel', 'purchase_channel__channel', 'creative', 'post', 'post__channel'
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'project',
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'project__channel',
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'purchase_channel',
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'purchase_channel__channel',
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'purchase_channel__purchase',
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'creative',
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'post',
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'post__channel',
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)
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.order_by('-wanted_placement_date')
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.all()
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@@ -93,3 +93,27 @@ async def get_overview_analytics(
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project_id=project_id,
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)
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return await deps.get_usecase().get_overview_analytics(input)
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@analytics_router.get('/projects')
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async def get_projects_analytics(
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workspace_id: uuid.UUID,
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current_user: Annotated[JWTPayload, Depends(deps.get_current_user)],
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project_ids: list[uuid.UUID] | None = None,
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date_from: datetime.datetime | None = None,
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date_to: datetime.datetime | None = None,
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grouping: dto.DateGrouping = dto.DateGrouping.DAY,
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date_grouping: dto.DateGroupingType = dto.DateGroupingType.PLACEMENT_DATE,
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metrics: list[dto.ProjectMetrics] | None = None,
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) -> dto.GetProjectsAnalyticsOutput:
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input = dto.GetProjectsAnalyticsInput(
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user_id=current_user.user_id,
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workspace_id=workspace_id,
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project_ids=project_ids,
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date_from=date_from,
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date_to=date_to,
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grouping=grouping,
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date_grouping=date_grouping,
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metrics=metrics,
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)
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return await deps.get_usecase().get_projects_analytics(input)
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@@ -62,6 +62,12 @@ __all__ = (
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'GetOverviewAnalyticsOutput',
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'GetSpendingAnalyticsInput',
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'GetSpendingAnalyticsOutput',
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'DateGroupingType',
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'ProjectMetrics',
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'ProjectMetricsData',
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'ProjectAnalyticsPeriod',
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'GetProjectsAnalyticsInput',
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'GetProjectsAnalyticsOutput',
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'WorkspaceMembershipOutput',
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'GetWorkspacesOutput',
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'CreateWorkspaceInput',
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@@ -86,6 +92,7 @@ from .analytics import (
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ChannelAnalyticsOutput,
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CreativeAnalyticsOutput,
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DateGrouping,
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DateGroupingType,
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GetChannelAnalyticsInput,
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GetChannelAnalyticsOutput,
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GetCreativesAnalyticsInput,
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@@ -93,6 +100,8 @@ from .analytics import (
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GetPlacementsAnalyticsInput,
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GetPlacementsAnalyticsOutput,
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GetOverviewAnalyticsInput,
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GetProjectsAnalyticsInput,
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GetProjectsAnalyticsOutput,
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GetSpendingAnalyticsInput,
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GetSpendingAnalyticsOutput,
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GetOverviewAnalyticsOutput,
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@@ -101,6 +110,9 @@ from .analytics import (
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OverviewDailyPoint,
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OverviewChannelPerformance,
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OverviewProjectSpending,
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ProjectAnalyticsPeriod,
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ProjectMetrics,
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ProjectMetricsData,
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SpendingDataPoint,
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)
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from .channel import (
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@@ -13,6 +13,27 @@ class DateGrouping(StrEnum):
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YEAR = 'year'
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class DateGroupingType(StrEnum):
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PURCHASE_DATE = 'purchase_date'
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LINK_DATE = 'link_date'
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PLACEMENT_DATE = 'placement_date'
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class ProjectMetrics(StrEnum):
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TOTAL_COST = 'total_cost'
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PURCHASES_COUNT = 'purchases_count'
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TOTAL_SUBSCRIPTIONS = 'total_subscriptions'
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TOTAL_VIEWS = 'total_views'
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AVG_CPF = 'avg_cpf'
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AVG_CPM = 'avg_cpm'
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AVG_POST_COST = 'avg_post_cost'
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CLICKS_COUNT = 'clicks_count'
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REACH_VOLUME = 'reach_volume'
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TOTAL_DISCOUNTS = 'total_discounts'
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AVG_DISCOUNT_PERCENT = 'avg_discount_percent'
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AVG_CONVERSION = 'avg_conversion'
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class PlacementAnalyticsOutput(pydantic.BaseModel):
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id: uuid.UUID
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project_id: uuid.UUID
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@@ -157,3 +178,40 @@ class GetOverviewAnalyticsOutput(pydantic.BaseModel):
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top_channels_by_cpf: list[OverviewChannelPerformance]
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worst_channels_by_cpf: list[OverviewChannelPerformance]
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project_spending: list[OverviewProjectSpending]
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class ProjectMetricsData(pydantic.BaseModel):
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total_cost: float | None = None
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purchases_count: int | None = None
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total_subscriptions: int | None = None
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total_views: int | None = None
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avg_cpf: float | None = None
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avg_cpm: float | None = None
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avg_post_cost: float | None = None
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clicks_count: int | None = None
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reach_volume: int | None = None
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total_discounts: float | None = None
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avg_discount_percent: float | None = None
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avg_conversion: float | None = None
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class ProjectAnalyticsPeriod(pydantic.BaseModel):
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period: str
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period_label: str
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metrics: ProjectMetricsData
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class GetProjectsAnalyticsInput(pydantic.BaseModel):
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user_id: uuid.UUID
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workspace_id: uuid.UUID
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project_ids: list[uuid.UUID] | None = None
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date_from: datetime.datetime | None = None
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date_to: datetime.datetime | None = None
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grouping: DateGrouping = DateGrouping.DAY
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date_grouping: DateGroupingType = DateGroupingType.PLACEMENT_DATE
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metrics: list[ProjectMetrics] | None = None
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class GetProjectsAnalyticsOutput(pydantic.BaseModel):
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periods: list[ProjectAnalyticsPeriod]
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totals: ProjectMetricsData
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@@ -60,8 +60,26 @@ class WorkspaceMemberOutput(pydantic.BaseModel):
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permissions_map.setdefault(permission.permission, [])
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for scope in getattr(member, 'permission_scopes', []) or []:
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# Определяем тип и ID scope на основе заполненных полей
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scope_type = None
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scope_id = None
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if scope.project_id:
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scope_type = domain.PermissionScopeType.PROJECT
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scope_id = scope.project_id
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elif scope.creative_id:
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scope_type = domain.PermissionScopeType.CREATIVE
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scope_id = scope.creative_id
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elif scope.placement_id:
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scope_type = domain.PermissionScopeType.PLACEMENT
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scope_id = scope.placement_id
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elif scope.channel_id:
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scope_type = domain.PermissionScopeType.CHANNEL
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scope_id = scope.channel_id
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if scope_type and scope_id:
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permissions_map.setdefault(scope.permission, []).append(
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WorkspacePermissionScopeOutput(type=scope.scope_type, id=scope.scope_id)
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WorkspacePermissionScopeOutput(type=scope_type, id=scope_id)
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)
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return cls(
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@@ -12,6 +12,7 @@ from .analytics.get_channel_analytics import get_channel_analytics
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from .analytics.get_creatives_analytics import get_creatives_analytics
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from .analytics.get_overview_analytics import get_overview_analytics
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from .analytics.get_placements_analytics import get_placements_analytics
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from .analytics.get_projects_analytics import get_projects_analytics
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from .analytics.get_spending_analytics import get_spending_analytics
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from .auth.create_telegram_login_token import create_telegram_login_token
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from .auth.get_jwt_by_telegram_id import get_jwt_by_telegram_id
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@@ -446,6 +447,7 @@ class Usecase:
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get_placements_analytics = get_placements_analytics
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get_creatives_analytics = get_creatives_analytics
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get_channel_analytics = get_channel_analytics
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get_projects_analytics = get_projects_analytics
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get_spending_analytics = get_spending_analytics
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get_overview_analytics = get_overview_analytics
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get_workspaces = get_workspaces
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299
src/usecase/analytics/get_projects_analytics.py
Normal file
299
src/usecase/analytics/get_projects_analytics.py
Normal file
@@ -0,0 +1,299 @@
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import datetime
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from collections import defaultdict
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from dataclasses import dataclass
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from typing import TYPE_CHECKING
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from fastapi import HTTPException, status
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from src import domain, dto
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if TYPE_CHECKING:
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from .. import Usecase
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def _format_period(dt: datetime.datetime, grouping: dto.DateGrouping) -> str:
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match grouping:
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case dto.DateGrouping.DAY:
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return dt.strftime('%Y-%m-%d')
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case dto.DateGrouping.WEEK:
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# ISO week
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year, week, _ = dt.isocalendar()
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return f'{year}-W{week:02d}'
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case dto.DateGrouping.MONTH:
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return dt.strftime('%Y-%m')
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case dto.DateGrouping.QUARTER:
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quarter = (dt.month - 1) // 3 + 1
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return f'{dt.year}-Q{quarter}'
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case _:
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raise ValueError('Invalid date grouping')
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def _format_period_label(dt: datetime.datetime, grouping: dto.DateGrouping) -> str:
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match grouping:
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case dto.DateGrouping.DAY:
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# "1 дек" или "1 дек 2024"
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day = dt.day
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month_names = ['янв', 'фев', 'мар', 'апр', 'май', 'июн', 'июл', 'авг', 'сен', 'окт', 'ноя', 'дек']
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month = month_names[dt.month - 1]
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return f'{day} {month}'
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case dto.DateGrouping.WEEK:
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# "49 нед. 2024" или "1-7 дек"
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year, week, _ = dt.isocalendar()
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# Находим первый день недели (понедельник)
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days_since_monday = dt.weekday()
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week_start = dt - datetime.timedelta(days=days_since_monday)
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week_end = week_start + datetime.timedelta(days=6)
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month_names = ['янв', 'фев', 'мар', 'апр', 'май', 'июн', 'июл', 'авг', 'сен', 'окт', 'ноя', 'дек']
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if week_start.month == week_end.month:
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return f'{week_start.day}-{week_end.day} {month_names[week_start.month - 1]}'
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else:
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return f'{week_start.day} {month_names[week_start.month - 1]}-{week_end.day} {month_names[week_end.month - 1]}'
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case dto.DateGrouping.MONTH:
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# "дек 2024"
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month_names = ['янв', 'фев', 'мар', 'апр', 'май', 'июн', 'июл', 'авг', 'сен', 'окт', 'ноя', 'дек']
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return f'{month_names[dt.month - 1]} {dt.year}'
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case dto.DateGrouping.QUARTER:
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# "Q4 2024"
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quarter = (dt.month - 1) // 3 + 1
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return f'Q{quarter} {dt.year}'
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case _:
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raise ValueError('Invalid date grouping')
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def _get_grouping_date(placement: domain.Placement, date_grouping: dto.DateGroupingType) -> datetime.datetime:
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match date_grouping:
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case dto.DateGroupingType.PLACEMENT_DATE:
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return placement.wanted_placement_date
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case dto.DateGroupingType.PURCHASE_DATE:
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if placement.purchase_channel and placement.purchase_channel.purchase:
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return placement.purchase_channel.purchase.created_at
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return placement.wanted_placement_date # Fallback
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case dto.DateGroupingType.LINK_DATE:
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if placement.purchase_channel:
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return placement.purchase_channel.created_at
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return placement.wanted_placement_date # Fallback
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case _:
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return placement.wanted_placement_date
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@dataclass
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class PeriodMetrics:
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total_cost: float = 0.0
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purchases_count: int = 0
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total_subscriptions: int = 0
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total_views: int = 0
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clicks_count: int = 0
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reach_volume: int = 0
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total_discounts: float = 0.0
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discount_count: int = 0
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discount_sum: float = 0.0
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def _calculate_metrics(
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period_metrics: PeriodMetrics,
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requested_metrics: list[dto.ProjectMetrics] | None,
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) -> dto.ProjectMetricsData:
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all_metrics = requested_metrics is None or len(requested_metrics) == 0
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def should_include(metric: dto.ProjectMetrics) -> bool:
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return all_metrics or metric in requested_metrics
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metrics = dto.ProjectMetricsData()
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if should_include(dto.ProjectMetrics.TOTAL_COST):
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metrics.total_cost = period_metrics.total_cost
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if should_include(dto.ProjectMetrics.PURCHASES_COUNT):
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metrics.purchases_count = period_metrics.purchases_count
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if should_include(dto.ProjectMetrics.TOTAL_SUBSCRIPTIONS):
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metrics.total_subscriptions = period_metrics.total_subscriptions
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if should_include(dto.ProjectMetrics.TOTAL_VIEWS):
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metrics.total_views = period_metrics.total_views
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if should_include(dto.ProjectMetrics.CLICKS_COUNT):
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metrics.clicks_count = period_metrics.clicks_count
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if should_include(dto.ProjectMetrics.REACH_VOLUME):
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metrics.reach_volume = period_metrics.reach_volume
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if should_include(dto.ProjectMetrics.TOTAL_DISCOUNTS):
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metrics.total_discounts = period_metrics.total_discounts
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# Средние значения
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if should_include(dto.ProjectMetrics.AVG_CPF):
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metrics.avg_cpf = (
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period_metrics.total_cost / period_metrics.total_subscriptions
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if period_metrics.total_subscriptions > 0 and period_metrics.total_cost > 0
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else None
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)
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if should_include(dto.ProjectMetrics.AVG_CPM):
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metrics.avg_cpm = (
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(period_metrics.total_cost / period_metrics.total_views) * 1000
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if period_metrics.total_views > 0 and period_metrics.total_cost > 0
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else None
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)
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if should_include(dto.ProjectMetrics.AVG_POST_COST):
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metrics.avg_post_cost = (
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period_metrics.total_cost / period_metrics.purchases_count
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if period_metrics.purchases_count > 0 and period_metrics.total_cost > 0
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else None
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)
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if should_include(dto.ProjectMetrics.AVG_DISCOUNT_PERCENT):
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if period_metrics.discount_count > 0:
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metrics.avg_discount_percent = period_metrics.discount_sum / period_metrics.discount_count
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else:
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metrics.avg_discount_percent = 0.0
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if should_include(dto.ProjectMetrics.AVG_CONVERSION):
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# Конверсия = подписки / просмотры * 100
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metrics.avg_conversion = (
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(period_metrics.total_subscriptions / period_metrics.total_views) * 100
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if period_metrics.total_views > 0 and period_metrics.total_subscriptions > 0
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else 0.0
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)
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return metrics
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async def get_projects_analytics(
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self: 'Usecase', input: dto.GetProjectsAnalyticsInput
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) -> dto.GetProjectsAnalyticsOutput:
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if input.date_from and input.date_to and input.date_from > input.date_to:
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raise HTTPException(status.HTTP_400_BAD_REQUEST, 'date_from must be before date_to')
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context = await self.ensure_workspace_permission(
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input.workspace_id, input.user_id, domain.PermissionKey.ANALYTICS_READ
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)
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allowed_project_ids = context.allowed_project_ids(domain.PermissionKey.ANALYTICS_READ)
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# Фильтрация по project_ids если указаны
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if input.project_ids:
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if allowed_project_ids is not None:
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# Пересечение разрешенных и запрошенных
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filtered_ids = [pid for pid in input.project_ids if pid in allowed_project_ids]
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if not filtered_ids:
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return dto.GetProjectsAnalyticsOutput(periods=[], totals=dto.ProjectMetricsData())
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allowed_project_ids = set(filtered_ids)
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else:
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allowed_project_ids = set(input.project_ids)
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placements = await self.database.get_workspace_placements(
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input.workspace_id,
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project_id=None,
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include_archived=False,
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allowed_project_ids=allowed_project_ids,
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date_from=input.date_from,
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date_to=input.date_to,
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)
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# Фильтрация по датам на основе date_grouping
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filtered_placements = []
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for placement in placements:
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grouping_date = _get_grouping_date(placement, input.date_grouping)
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if input.date_from and grouping_date < input.date_from:
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continue
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if input.date_to and grouping_date > input.date_to:
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continue
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filtered_placements.append(placement)
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# Batch fetch views data
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post_ids = [p.post.id for p in filtered_placements if p.post]
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views_map = await self.database.get_latest_views_data_batch(post_ids) if post_ids else {}
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# Batch fetch subscriptions counts
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placement_ids = [p.id for p in filtered_placements]
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subscriptions_counts = await self.database.count_subscriptions_by_placement_batch(placement_ids)
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# Группировка по периодам
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period_data: dict[str, PeriodMetrics] = defaultdict(PeriodMetrics)
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total_metrics = PeriodMetrics()
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for placement in filtered_placements:
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grouping_date = _get_grouping_date(placement, input.date_grouping)
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period = _format_period(grouping_date, input.grouping)
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pd = period_data[period]
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# Обновляем метрики периода
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pd.purchases_count += 1
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total_metrics.purchases_count += 1
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cost = placement.cost or 0.0
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pd.total_cost += cost
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total_metrics.total_cost += cost
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subs_count = subscriptions_counts.get(placement.id, 0)
|
||||
pd.total_subscriptions += subs_count
|
||||
pd.clicks_count += subs_count
|
||||
total_metrics.total_subscriptions += subs_count
|
||||
total_metrics.clicks_count += subs_count
|
||||
|
||||
views_count = 0
|
||||
if placement.post and placement.post.id in views_map:
|
||||
views_count = views_map[placement.post.id][0]
|
||||
pd.total_views += views_count
|
||||
pd.reach_volume += views_count
|
||||
total_metrics.total_views += views_count
|
||||
total_metrics.reach_volume += views_count
|
||||
|
||||
# Расчет скидок
|
||||
purchase_channel = placement.purchase_channel
|
||||
if purchase_channel and purchase_channel.cost_before_bargain and purchase_channel.cost_before_bargain > cost:
|
||||
discount = purchase_channel.cost_before_bargain - cost
|
||||
discount_percent = (discount / purchase_channel.cost_before_bargain) * 100 if purchase_channel.cost_before_bargain > 0 else 0.0
|
||||
|
||||
pd.total_discounts += discount
|
||||
pd.discount_count += 1
|
||||
pd.discount_sum += discount_percent
|
||||
|
||||
total_metrics.total_discounts += discount
|
||||
total_metrics.discount_count += 1
|
||||
total_metrics.discount_sum += discount_percent
|
||||
|
||||
# Формируем периоды с метриками
|
||||
periods: list[dto.ProjectAnalyticsPeriod] = []
|
||||
for period_key in sorted(period_data.keys()):
|
||||
pd = period_data[period_key]
|
||||
|
||||
# Определяем дату для period_label (берем первую дату периода)
|
||||
if input.grouping == dto.DateGrouping.DAY:
|
||||
period_dt = datetime.datetime.strptime(period_key, '%Y-%m-%d')
|
||||
elif input.grouping == dto.DateGrouping.WEEK:
|
||||
# ISO week format: YYYY-Www
|
||||
year, week_str = period_key.split('-W')
|
||||
week = int(week_str)
|
||||
# Находим первый день недели (понедельник) для данной ISO недели
|
||||
jan4 = datetime.datetime(int(year), 1, 4)
|
||||
jan4_weekday = jan4.weekday() # 0=Monday, 6=Sunday
|
||||
days_since_monday = (jan4_weekday + 1) % 7
|
||||
jan4_monday = jan4 - datetime.timedelta(days=days_since_monday)
|
||||
period_dt = jan4_monday + datetime.timedelta(weeks=week - 1)
|
||||
elif input.grouping == dto.DateGrouping.MONTH:
|
||||
period_dt = datetime.datetime.strptime(period_key, '%Y-%m')
|
||||
elif input.grouping == dto.DateGrouping.QUARTER:
|
||||
year, quarter = period_key.split('-Q')
|
||||
month = (int(quarter) - 1) * 3 + 1
|
||||
period_dt = datetime.datetime(int(year), month, 1)
|
||||
else:
|
||||
period_dt = datetime.datetime.now()
|
||||
|
||||
period_label = _format_period_label(period_dt, input.grouping)
|
||||
metrics = _calculate_metrics(pd, input.metrics)
|
||||
|
||||
periods.append(
|
||||
dto.ProjectAnalyticsPeriod(
|
||||
period=period_key,
|
||||
period_label=period_label,
|
||||
metrics=metrics,
|
||||
)
|
||||
)
|
||||
|
||||
totals = _calculate_metrics(total_metrics, input.metrics)
|
||||
|
||||
return dto.GetProjectsAnalyticsOutput(periods=periods, totals=totals)
|
||||
|
||||
Reference in New Issue
Block a user