oqyude
363d440d53
- All domain monetary fields now use Decimal: - Account.balance, Asset.value, Asset.growth_rate - Liability.balance, Liability.interest, Liability.payment - Transaction.amount, RecurringCashflow.amount - ExchangeRate.rate - ForecastScenario.income_multiplier, expense_multiplier, growth_multiplier - CurrencyConverter: all arithmetic in Decimal, quantize to 0.01 with ROUND_HALF_UP - ForecastService: Decimal arithmetic throughout (income, expenses, balance, growth, liability cost) - ScenarioService: Decimal multipliers, deepcopy safe with Decimal fields - assistant.py: _DecimalEncoder for json.dumps (Decimal -> str in JSON) Pydantic v2 + Decimal: - model_dump(mode='json') converts Decimal to str (JSON-safe) - model_validate() parses str back to Decimal - Round-trip preserves precision (100.50 stays 100.50) Tests: 63/63 pass.
116 lines
3.8 KiB
Python
116 lines
3.8 KiB
Python
from copy import deepcopy
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from decimal import Decimal, ROUND_HALF_UP
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from domain import Account, FinancialModel
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class ForecastError(Exception):
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pass
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_ZERO = Decimal("0")
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_ONE = Decimal("1")
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_TWELVE = Decimal("12")
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_HUNDRED = Decimal("100")
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class ForecastService:
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def __init__(self, model: FinancialModel):
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self.model = deepcopy(model)
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def forecast_cashflow(self, months: int = 12) -> list[dict]:
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if months < 1:
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raise ForecastError("months must be >= 1")
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results = []
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for account in self.model.accounts:
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monthly = self._project_account(account, months)
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for m in range(months):
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results.append({
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"account": account.name,
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"month": m + 1,
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"balance": monthly[m]["balance"],
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"income": monthly[m]["income"],
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"expenses": monthly[m]["expenses"],
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})
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# Asset growth — once per month, distributed across accounts proportionally
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for m in range(months):
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total_growth = sum(
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a.value * a.growth_rate / _HUNDRED / _TWELVE
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for a in self.model.assets
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)
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month_rows = [r for r in results if r["month"] == m + 1]
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total_bal = sum(r["balance"] for r in month_rows) or _ONE
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for r in month_rows:
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share = r["balance"] / total_bal
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r["income"] = _q(r["income"] + total_growth * share)
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r["balance"] = _q(r["balance"] + total_growth * share)
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# Compound asset values for next month
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for a in self.model.assets:
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a.value = a.value + a.value * a.growth_rate / _HUNDRED / _TWELVE
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return results
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def _project_account(self, account: Account, months: int) -> list[dict]:
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balance = account.balance
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monthly = []
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for m in range(months):
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income = _ZERO
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expenses = _ZERO
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for t in self.model.transactions:
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if t.account == str(account.id):
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if t.amount > 0:
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income += t.amount
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else:
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expenses += abs(t.amount)
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for r in self.model.recurring:
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if r.amount > 0:
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income += r.amount
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else:
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expenses += abs(r.amount)
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expenses += self._liability_cost(account)
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balance = balance + income - expenses
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monthly.append({
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"balance": _q(balance),
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"income": _q(income),
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"expenses": _q(expenses),
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})
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return monthly
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def _liability_cost(self, account: Account) -> Decimal:
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total = _ZERO
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for liability in self.model.liabilities:
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interest_cost = liability.balance * liability.interest / _HUNDRED / _TWELVE
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total += interest_cost
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liability.balance = liability.balance - (liability.payment - interest_cost)
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if liability.balance < 0:
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liability.balance = _ZERO
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return total
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def summary(self, months: int = 12) -> dict:
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results = self.forecast_cashflow(months)
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if not results:
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return {"total_balance": 0, "total_income": 0, "total_expenses": 0, "months": months}
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final = results[-1]
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all_income = sum(r["income"] for r in results)
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all_expenses = sum(r["expenses"] for r in results)
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return {
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"total_balance": final["balance"],
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"total_income": _q(all_income),
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"total_expenses": _q(all_expenses),
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"months": months,
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}
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def _q(v: Decimal) -> Decimal:
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"""Quantize to 2 decimal places, ROUND_HALF_UP."""
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return v.quantize(Decimal("0.01"), rounding=ROUND_HALF_UP)
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