# tests/services/test_forecasting.py
import datetime
from sqlalchemy import create_engine
from sqlalchemy.orm import Session

from src.db import Base
from src.models import *
from src.seed import seed_categories
from src.services.forecasting import ForecastingService


def make_session():
    engine = create_engine("sqlite:///:memory:")
    Base.metadata.create_all(engine)
    return Session(engine)


def make_forecast_data(session):
    seed_categories(session)
    member = HouseholdMember(name="Andrew", relationship="self")
    session.add(member)
    session.flush()
    account = Account(name="Chase", institution="Chase", account_type="credit", owner_id=member.id)
    session.add(account)
    session.flush()
    groceries = session.query(Category).filter_by(name="Groceries").one()

    # 3 months of grocery spending: $500, $600, $700 (trending up)
    for month, total in [(10, 500), (11, 600), (12, 700)]:
        session.add(Transaction(
            date=datetime.date(2025, month, 15),
            amount=-total,
            description="GROCERIES",
            account_id=account.id,
            category_id=groceries.id,
            tag="needs",
        ))
    session.commit()
    return account


def test_monthly_forecast():
    session = make_session()
    make_forecast_data(session)
    svc = ForecastingService(session)
    forecast = svc.forecast_month()
    groceries = [f for f in forecast if f["category"] == "Groceries"]
    assert len(groceries) == 1
    assert groceries[0]["projected"] < 0


def test_annual_forecast():
    session = make_session()
    make_forecast_data(session)
    svc = ForecastingService(session)
    forecast = svc.forecast_year()
    assert len(forecast) > 0
    total = sum(f["projected"] for f in forecast)
    assert total < 0


def test_what_if_removes_recurring():
    session = make_session()
    make_forecast_data(session)
    svc = ForecastingService(session)
    base = svc.forecast_month()
    adjusted = svc.forecast_month(exclude_descriptions=["GROCERIES"])
    base_total = sum(f["projected"] for f in base)
    adj_total = sum(f["projected"] for f in adjusted)
    assert adj_total > base_total  # Less spending when we exclude