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09a0e383e0
Two of the four ideas picked from the Maybe/Sure feature audit: - Idle cash: a 5th proactive alert flags a depository account (checking/ savings/cash) sitting at or above a configurable balance with no transaction touching it for a configurable number of days. - Category hierarchy: categories can now have one level of subcategories (Groceries -> Alcohol). Dashboard/report aggregations roll a subcategory's spending into its parent's slice. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
102 lines
4.0 KiB
Python
102 lines
4.0 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 sqlalchemy.orm import aliased
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from app.models.category import Category
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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 CategoryBreakdownItem, DashboardSummary
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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 — Parent is a
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# self-join to resolve each transaction's *top-level* category, falling
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# back to the transaction's own category when it has no parent.
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Parent = aliased(Category)
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effective_id = func.coalesce(Category.parent_id, Category.id)
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effective_name = func.coalesce(Parent.name, Category.name)
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effective_color = func.coalesce(Parent.color, Category.color)
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effective_icon = func.coalesce(Parent.icon, Category.icon)
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effective_sort = func.coalesce(Parent.sort_order, Category.sort_order)
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breakdown_stmt = (
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select(
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effective_id.label("category_id"),
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effective_name.label("name"),
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effective_color.label("color"),
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effective_icon.label("icon"),
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func.coalesce(func.sum(Transaction.amount), 0).label("amount"),
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)
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.join(Category, Category.id == Transaction.category_id)
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.outerjoin(Parent, Parent.id == Category.parent_id)
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.where(
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Transaction.date >= start,
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Transaction.date <= end,
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Transaction.type == TransactionType.EXPENSE,
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)
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.group_by(effective_id, effective_name, effective_color, effective_icon, effective_sort)
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.order_by(func.sum(Transaction.amount).desc(), effective_sort)
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)
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breakdown_result = await session.execute(breakdown_stmt)
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rows = breakdown_result.all()
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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=cat_id, name=name, color=color, icon=icon, amount=amount, percent=_percent(amount)
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)
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for cat_id, name, color, icon, amount 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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