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Раньше сплит позволял смешивать вообще любые категории. Реальная задача — разложить одну покупку по подкатегориям ОДНОЙ базовой категории (100 € на продукты: сколько на сладости, сколько на уход). А раз Dashboard и рейтинг категорий сворачивают подкатегории в родителя, эта разбивка нигде не была видна. - _build_splits() требует, чтобы все категории сплита были одной родительской категорией или её прямыми подкатегориями. - category_rollup.py отдаёт для каждого родительского тотала список category-источников, которые в него скинулись (children) — пусто, если источник один. - Dashboard и рейтинг категорий: строка с непустым children раскрывается по клику, показывая вклад каждой подкатегории. - Форма транзакции: выбор категории при сплите — сначала базовая (верхний уровень), затем строки сплита выбирают саму базовую или её подкатегорию.
86 lines
3.3 KiB
Python
86 lines
3.3 KiB
Python
"""Aggregation logic behind the Overview dashboard."""
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import calendar
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from datetime import date
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from decimal import Decimal
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from sqlalchemy import func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.enums import TransactionType
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from app.models.transaction import Transaction
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from app.schemas.dashboard import CategoryBreakdownChildItem, CategoryBreakdownItem, DashboardSummary
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from app.services.category_rollup import rollup_spending_by_top_level_category
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# Categorical slots are capped at 8 (dataviz skill: a 9th series folds into "Other",
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# never a generated hue) — this is also the exact size of the default category set.
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MAX_CHART_SLICES = 8
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OTHER_SLICE_COLOR = "#898781" # muted ink, reserved for the non-categorical rollup
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def _month_bounds(year: int, month: int) -> tuple[date, date]:
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last_day = calendar.monthrange(year, month)[1]
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return date(year, month, 1), date(year, month, last_day)
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async def get_dashboard_summary(session: AsyncSession, year: int, month: int) -> DashboardSummary:
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start, end = _month_bounds(year, month)
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totals_stmt = (
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select(Transaction.type, func.coalesce(func.sum(Transaction.amount), 0))
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.where(Transaction.date >= start, Transaction.date <= end)
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.group_by(Transaction.type)
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)
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totals_result = await session.execute(totals_stmt)
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totals: dict[TransactionType, Decimal] = {row[0]: row[1] for row in totals_result.all()}
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real_income = totals.get(TransactionType.INCOME, Decimal("0"))
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spent = totals.get(TransactionType.EXPENSE, Decimal("0"))
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transferred_out = totals.get(TransactionType.TRANSFER, Decimal("0"))
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# A subcategory's spending rolls up into its parent's slice, and a split
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# transaction's category_id=NULL means its category lives on its split
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# lines instead — rollup_spending_by_top_level_category handles both
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# the same way a plain transaction's category already was.
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rows = await rollup_spending_by_top_level_category(
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session, transaction_type=TransactionType.EXPENSE, start_date=start, end_date=end
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)
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top_rows, rest_rows = rows[:MAX_CHART_SLICES], rows[MAX_CHART_SLICES:]
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def _percent(amount: Decimal) -> float:
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return float(amount / spent * 100) if spent else 0.0
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spending_by_category = [
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CategoryBreakdownItem(
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category_id=row.category_id, name=row.name, color=row.color, icon=row.icon,
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amount=row.amount, percent=_percent(row.amount),
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children=[
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CategoryBreakdownChildItem(
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category_id=child.category_id, name=child.name, color=child.color, icon=child.icon,
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amount=child.amount,
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)
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for child in row.children
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],
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)
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for row in top_rows
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]
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if rest_rows:
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other_amount = sum((row.amount for row in rest_rows), Decimal("0"))
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spending_by_category.append(
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CategoryBreakdownItem(
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category_id=None, name="Other", color=OTHER_SLICE_COLOR, icon="more-horizontal",
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amount=other_amount, percent=_percent(other_amount),
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)
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)
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return DashboardSummary(
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year=year,
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month=month,
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real_income=real_income,
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spent=spent,
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net=real_income - spent,
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transferred_out=transferred_out,
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spending_by_category=spending_by_category,
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)
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