Merge pull request #2 from TelegramExchange/feat/projects-analytics
feat: add projects analytics endpoint
This commit is contained in:
Artem
@@ -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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@@ -450,6 +451,7 @@ 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
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299
src/usecase/analytics/get_projects_analytics.py
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@@ -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)
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pd.total_subscriptions += subs_count
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pd.clicks_count += subs_count
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total_metrics.total_subscriptions += subs_count
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total_metrics.clicks_count += subs_count
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views_count = 0
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if placement.post and placement.post.id in views_map:
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views_count = views_map[placement.post.id][0]
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pd.total_views += views_count
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pd.reach_volume += views_count
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total_metrics.total_views += views_count
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total_metrics.reach_volume += views_count
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# Расчет скидок
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purchase_channel = placement.purchase_channel
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if purchase_channel and purchase_channel.cost_before_bargain and purchase_channel.cost_before_bargain > cost:
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discount = purchase_channel.cost_before_bargain - cost
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discount_percent = (discount / purchase_channel.cost_before_bargain) * 100 if purchase_channel.cost_before_bargain > 0 else 0.0
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pd.total_discounts += discount
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pd.discount_count += 1
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pd.discount_sum += discount_percent
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total_metrics.total_discounts += discount
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total_metrics.discount_count += 1
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total_metrics.discount_sum += discount_percent
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# Формируем периоды с метриками
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periods: list[dto.ProjectAnalyticsPeriod] = []
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for period_key in sorted(period_data.keys()):
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pd = period_data[period_key]
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# Определяем дату для period_label (берем первую дату периода)
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if input.grouping == dto.DateGrouping.DAY:
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period_dt = datetime.datetime.strptime(period_key, '%Y-%m-%d')
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elif input.grouping == dto.DateGrouping.WEEK:
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# ISO week format: YYYY-Www
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year, week_str = period_key.split('-W')
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week = int(week_str)
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# Находим первый день недели (понедельник) для данной ISO недели
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jan4 = datetime.datetime(int(year), 1, 4)
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jan4_weekday = jan4.weekday() # 0=Monday, 6=Sunday
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days_since_monday = (jan4_weekday + 1) % 7
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jan4_monday = jan4 - datetime.timedelta(days=days_since_monday)
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period_dt = jan4_monday + datetime.timedelta(weeks=week - 1)
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elif input.grouping == dto.DateGrouping.MONTH:
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period_dt = datetime.datetime.strptime(period_key, '%Y-%m')
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elif input.grouping == dto.DateGrouping.QUARTER:
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year, quarter = period_key.split('-Q')
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month = (int(quarter) - 1) * 3 + 1
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period_dt = datetime.datetime(int(year), month, 1)
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else:
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period_dt = datetime.datetime.now()
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period_label = _format_period_label(period_dt, input.grouping)
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metrics = _calculate_metrics(pd, input.metrics)
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periods.append(
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dto.ProjectAnalyticsPeriod(
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period=period_key,
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period_label=period_label,
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metrics=metrics,
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)
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)
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totals = _calculate_metrics(total_metrics, input.metrics)
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return dto.GetProjectsAnalyticsOutput(periods=periods, totals=totals)
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