- app/integrations/pricing: profiles.py (pydantic ManualProfile/TibberProfile, load_profile/list_profiles/validate_values), manual.yaml + tibber.yaml (structure-only, no price values), strategies.py (register/get_strategy, manual dual-tariff + tibber strategies, all Decimal). - tibber strategy matches nearest tibber_price with starts_at <= t0. - tests for profiles + strategies (hand-checked dual-tariff & tibber math).
554 lines
21 KiB
Python
554 lines
21 KiB
Python
"""Tests for app/integrations/pricing/strategies.py.
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Acceptance criteria covered
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----------------------------
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1. ``get_strategy("manual")`` / ``get_strategy("tibber")`` return registered callables.
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2. Manual strategy: dual-tariff import/export/net calculated correctly (hand-verified).
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3. Manual strategy: Decimal precision — no float binary rounding errors.
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4. Tibber strategy: queries the most recent TibberPrice with starts_at ≤ t0.
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5. Tibber strategy: buy=total, sell=total−energy_tax−sell_adjust.
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6. Tibber strategy: negative total → negative export_revenue (not clamped).
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7. Tibber strategy: raises TibberPriceNotFoundError when no matching row exists.
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8. ``register_strategy`` / ``get_strategy`` round-trip works.
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9. ``get_strategy`` raises KeyError for unknown kinds.
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"""
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from __future__ import annotations
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from datetime import datetime, timezone
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from decimal import Decimal
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from pathlib import Path
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import pytest
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from alembic import command
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from alembic.config import Config
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from sqlalchemy import create_engine
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from sqlalchemy.orm import Session
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from app.integrations.pricing.strategies import (
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PeriodDeltas,
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TibberPriceNotFoundError,
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get_strategy,
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register_strategy,
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)
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from app.models.energy import TibberPrice
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# ---------------------------------------------------------------------------
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# Fixtures: in-memory / temp-file SQLite with energy tables
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# ---------------------------------------------------------------------------
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def _make_app_alembic_config(database_url: str) -> Config:
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cfg = Config("alembic_app.ini")
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cfg.set_main_option("sqlalchemy.url", database_url)
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return cfg
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@pytest.fixture()
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def tibber_db(tmp_path: Path):
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"""Temporary SQLite DB upgraded to head (has tibber_price table)."""
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db_path = tmp_path / "tibber_strategy_test.db"
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db_url = f"sqlite:///{db_path}"
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alembic_cfg = _make_app_alembic_config(db_url)
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command.upgrade(alembic_cfg, "head")
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engine = create_engine(db_url, connect_args={"check_same_thread": False})
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yield engine
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engine.dispose()
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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_UTC = timezone.utc
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def _ts(hour: int, minute: int = 0) -> datetime:
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"""Return a UTC datetime on 2026-06-23 at the given hour:minute."""
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return datetime(2026, 6, 23, hour, minute, 0, tzinfo=_UTC)
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def _insert_tibber_price(
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session: Session,
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starts_at: datetime,
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total: float,
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energy: float = 0.08,
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tax: float | None = None,
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currency: str = "EUR",
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) -> TibberPrice:
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"""Insert and flush a TibberPrice row; return the ORM instance."""
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if tax is None:
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tax = round(total - energy, 6)
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row = TibberPrice(
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starts_at=starts_at,
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resolution="QUARTER_HOURLY",
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energy=energy,
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tax=tax,
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total=total,
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level="NORMAL",
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currency=currency,
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fetched_at=datetime.now(_UTC),
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)
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session.add(row)
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session.flush()
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return row
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# ---------------------------------------------------------------------------
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# 1. Registry round-trip
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# ---------------------------------------------------------------------------
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class TestRegistry:
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def test_manual_strategy_registered(self) -> None:
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fn = get_strategy("manual")
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assert callable(fn)
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def test_tibber_strategy_registered(self) -> None:
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fn = get_strategy("tibber")
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assert callable(fn)
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def test_unknown_kind_raises_key_error(self) -> None:
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with pytest.raises(KeyError, match="no_such_kind"):
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get_strategy("no_such_kind")
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def test_register_and_retrieve_custom_strategy(self) -> None:
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def _my_fn(deltas, t0, values, session):
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return {}
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register_strategy("_test_custom", _my_fn)
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assert get_strategy("_test_custom") is _my_fn
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# Cleanup to avoid polluting other tests.
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from app.integrations.pricing.strategies import _REGISTRY
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_REGISTRY.pop("_test_custom", None)
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# ---------------------------------------------------------------------------
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# 2-3. Manual strategy
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# ---------------------------------------------------------------------------
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# Dummy session (manual strategy does not use the session).
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_NO_SESSION = None # type: ignore[assignment]
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class TestManualStrategy:
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"""Verify manual dual-tariff price calculations."""
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# Contract values for all manual tests.
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_VALUES = {
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"energy": {
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"buy": {"normal": 0.133, "dal": 0.127},
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"sell": {"normal": 0.05, "dal": 0.05},
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"energy_tax": 0.11,
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"ode": 0.0,
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},
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"standing": {"network_fee": 9.87, "management_fee": 9.87},
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"credits": {"heffingskorting": 600.0},
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}
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def _call(self, deltas: PeriodDeltas) -> dict:
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fn = get_strategy("manual")
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return fn(deltas, _ts(10), self._VALUES, _NO_SESSION)
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# --- hand-calculated expected values ---
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# buy_dal = 0.127 + 0.11 + 0.0 = 0.237
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# buy_normal = 0.133 + 0.11 + 0.0 = 0.243
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# sell_dal = 0.05
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# sell_normal = 0.05
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#
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# With Δd1=2, Δd2=3, Δr1=1, Δr2=4:
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# import_cost = 2×0.237 + 3×0.243 = 0.474 + 0.729 = 1.203
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# export_revenue = 1×0.05 + 4×0.05 = 0.05 + 0.20 = 0.25
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# net_cost = 1.203 − 0.25 = 0.953
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def test_import_cost_dual_tariff(self) -> None:
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deltas = PeriodDeltas(
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d1=Decimal("2"), d2=Decimal("3"),
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r1=Decimal("1"), r2=Decimal("4"),
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)
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result = self._call(deltas)
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expected = Decimal("2") * Decimal("0.237") + Decimal("3") * Decimal("0.243")
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assert result["import_cost"] == expected
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def test_export_revenue_dual_tariff(self) -> None:
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deltas = PeriodDeltas(
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d1=Decimal("2"), d2=Decimal("3"),
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r1=Decimal("1"), r2=Decimal("4"),
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)
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result = self._call(deltas)
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expected = Decimal("1") * Decimal("0.05") + Decimal("4") * Decimal("0.05")
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assert result["export_revenue"] == expected
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def test_net_cost_equals_import_minus_export(self) -> None:
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deltas = PeriodDeltas(
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d1=Decimal("2"), d2=Decimal("3"),
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r1=Decimal("1"), r2=Decimal("4"),
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)
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result = self._call(deltas)
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assert result["net_cost"] == result["import_cost"] - result["export_revenue"]
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def test_hand_calculated_values(self) -> None:
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"""Verify exact hand-calculated result for the reference deltas."""
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deltas = PeriodDeltas(
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d1=Decimal("2"), d2=Decimal("3"),
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r1=Decimal("1"), r2=Decimal("4"),
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)
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result = self._call(deltas)
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assert result["import_cost"] == Decimal("1.203")
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assert result["export_revenue"] == Decimal("0.25")
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assert result["net_cost"] == Decimal("0.953")
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def test_zero_deltas_yields_zero_costs(self) -> None:
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deltas = PeriodDeltas(
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d1=Decimal("0"), d2=Decimal("0"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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result = self._call(deltas)
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assert result["import_cost"] == Decimal("0")
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assert result["export_revenue"] == Decimal("0")
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assert result["net_cost"] == Decimal("0")
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def test_ode_included_in_buy_price(self) -> None:
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"""When ode > 0 it is added to the effective buy price."""
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values = {
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"energy": {
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"buy": {"normal": 0.10, "dal": 0.10},
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"sell": {"normal": 0.05, "dal": 0.05},
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"energy_tax": 0.10,
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"ode": 0.01, # non-zero ode
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},
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"standing": {"network_fee": 0.0, "management_fee": 0.0},
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"credits": {"heffingskorting": 0.0},
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}
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("0"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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fn = get_strategy("manual")
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result = fn(deltas, _ts(10), values, _NO_SESSION)
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# buy_dal = 0.10 + 0.10 + 0.01 = 0.21; import_cost = 1 × 0.21 = 0.21
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assert result["import_cost"] == Decimal("0.21")
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def test_import_export_kept_separate(self) -> None:
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"""import_cost and export_revenue must not be netted before assignment."""
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deltas = PeriodDeltas(
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d1=Decimal("5"), d2=Decimal("5"),
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r1=Decimal("3"), r2=Decimal("3"),
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)
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result = self._call(deltas)
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# Both must be individually non-zero.
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assert result["import_cost"] > 0
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assert result["export_revenue"] > 0
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def test_pricing_snapshot_present(self) -> None:
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("1"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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result = self._call(deltas)
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snapshot = result["pricing"]
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assert snapshot["kind"] == "manual"
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assert "buy_dal" in snapshot
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assert "buy_normal" in snapshot
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assert "sell_dal" in snapshot
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assert "sell_normal" in snapshot
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# ---------------------------------------------------------------------------
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# 3. Decimal precision — float-error exposure test
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# ---------------------------------------------------------------------------
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class TestManualDecimalPrecision:
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"""Use values known to produce binary float errors if float arithmetic is used."""
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def test_no_float_rounding_error(self) -> None:
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"""0.1 + 0.2 in float gives 0.30000000000000004; Decimal must be exact."""
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values = {
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"energy": {
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"buy": {"normal": 0.1, "dal": 0.2},
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"sell": {"normal": 0.1, "dal": 0.1},
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"energy_tax": 0.0,
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"ode": 0.0,
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},
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"standing": {"network_fee": 0.0, "management_fee": 0.0},
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"credits": {"heffingskorting": 0.0},
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}
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("1"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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fn = get_strategy("manual")
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result = fn(deltas, _ts(10), values, _NO_SESSION)
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# import_cost = 1×0.2 + 1×0.1 = 0.3 exactly
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assert result["import_cost"] == Decimal("0.3"), (
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f"Expected Decimal('0.3'), got {result['import_cost']!r} — "
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"float arithmetic leaking in?"
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)
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def test_result_values_are_decimal_type(self) -> None:
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values = {
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"energy": {
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"buy": {"normal": 0.133, "dal": 0.127},
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"sell": {"normal": 0.05, "dal": 0.05},
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"energy_tax": 0.11,
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"ode": 0.0,
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},
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"standing": {"network_fee": 9.87, "management_fee": 9.87},
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"credits": {"heffingskorting": 600.0},
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}
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("1"),
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r1=Decimal("1"), r2=Decimal("1"),
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)
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fn = get_strategy("manual")
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result = fn(deltas, _ts(10), values, _NO_SESSION)
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assert isinstance(result["import_cost"], Decimal)
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assert isinstance(result["export_revenue"], Decimal)
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assert isinstance(result["net_cost"], Decimal)
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# ---------------------------------------------------------------------------
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# 4-7. Tibber strategy
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# ---------------------------------------------------------------------------
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class TestTibberStrategy:
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"""Verify Tibber price-lookup and billing calculations."""
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_VALUES = {
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"energy": {
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"energy_tax": 0.10,
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"sell_adjust": 0.0,
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},
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"standing": {"management_fee": 5.99, "network_fee": 9.87},
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"credits": {"heffingskorting": 600.0},
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}
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def _call(
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self,
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deltas: PeriodDeltas,
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t0: datetime,
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session: Session,
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values: dict | None = None,
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) -> dict:
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fn = get_strategy("tibber")
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return fn(deltas, t0, values or self._VALUES, session)
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def test_buy_equals_total(self, tibber_db) -> None:
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t0 = _ts(10, 0)
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with Session(tibber_db) as session:
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.25)
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session.commit()
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("1"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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result = self._call(deltas, t0, session)
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# buy = total = 0.25; import_cost = 2 × 0.25 = 0.50
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assert result["import_cost"] == Decimal("2") * Decimal("0.25")
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def test_sell_equals_total_minus_energy_tax_minus_adjust(self, tibber_db) -> None:
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t0 = _ts(10, 0)
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with Session(tibber_db) as session:
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.25)
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session.commit()
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values = {
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"energy": {"energy_tax": 0.10, "sell_adjust": 0.02},
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"standing": {"management_fee": 5.99, "network_fee": 9.87},
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"credits": {"heffingskorting": 600.0},
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}
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("0"), d2=Decimal("0"),
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r1=Decimal("1"), r2=Decimal("1"),
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)
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result = self._call(deltas, t0, session, values=values)
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# sell = 0.25 - 0.10 - 0.02 = 0.13; export_revenue = 2 × 0.13 = 0.26
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assert result["export_revenue"] == Decimal("2") * Decimal("0.13")
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def test_uses_most_recent_price_before_t0(self, tibber_db) -> None:
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"""Correct row: starts_at ≤ t0, most recent wins."""
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t0 = _ts(10, 0)
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with Session(tibber_db) as session:
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# Older price (should NOT be used)
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_insert_tibber_price(session, starts_at=_ts(9, 0), total=0.10)
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# Closer price (starts_at ≤ t0, should be used)
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.30)
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# Future price (starts_at > t0, must NOT be used)
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_insert_tibber_price(session, starts_at=_ts(10, 15), total=0.99)
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session.commit()
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("0"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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result = self._call(deltas, t0, session)
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# Only the 09:45 price (total=0.30) should be used.
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snapshot = result["pricing"]
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assert Decimal(snapshot["total"]) == Decimal("0.30")
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def test_tibber_sums_both_tariff_registers(self, tibber_db) -> None:
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"""Tibber does not split dal/normal; import_cost = (d1+d2) × buy."""
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t0 = _ts(10, 0)
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with Session(tibber_db) as session:
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.20)
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session.commit()
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("3"), d2=Decimal("2"),
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r1=Decimal("0"), r2=Decimal("0"),
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)
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result = self._call(deltas, t0, session)
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# import_cost = (3+2) × 0.20 = 1.00
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assert result["import_cost"] == Decimal("1.00")
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def test_negative_total_gives_negative_export_revenue(self, tibber_db) -> None:
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"""When total is negative, selling electricity costs money (correct behaviour)."""
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t0 = _ts(10, 0)
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with Session(tibber_db) as session:
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# total = -0.05; sell = -0.05 - 0.10 - 0.0 = -0.15
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=-0.05)
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session.commit()
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("0"), d2=Decimal("0"),
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r1=Decimal("2"), r2=Decimal("2"),
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)
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result = self._call(deltas, t0, session)
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# sell = -0.05 - 0.10 - 0.0 = -0.15; export_revenue = 4 × (-0.15) = -0.60
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assert result["export_revenue"] < 0
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assert result["export_revenue"] == Decimal("4") * (
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Decimal("-0.05") - Decimal("0.10") - Decimal("0.0")
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)
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def test_negative_total_exact_calculation(self, tibber_db) -> None:
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"""Full hand-calculation for negative-total scenario."""
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t0 = _ts(10, 0)
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total = Decimal("-0.05")
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energy_tax = Decimal("0.10")
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sell_adjust = Decimal("0.0")
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with Session(tibber_db) as session:
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_insert_tibber_price(session, starts_at=_ts(9, 45), total=float(total))
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session.commit()
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with Session(tibber_db) as session:
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deltas = PeriodDeltas(
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d1=Decimal("1"), d2=Decimal("1"), # delivered = 2 kWh
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r1=Decimal("1"), r2=Decimal("1"), # returned = 2 kWh
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)
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result = self._call(deltas, t0, session)
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buy = total # -0.05
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sell = total - energy_tax - sell_adjust # -0.15
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expected_import = Decimal("2") * buy # -0.10
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expected_export = Decimal("2") * sell # -0.30
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expected_net = expected_import - expected_export # 0.20
|
||
|
||
assert result["import_cost"] == expected_import
|
||
assert result["export_revenue"] == expected_export
|
||
assert result["net_cost"] == expected_net
|
||
|
||
def test_no_price_before_t0_raises(self, tibber_db) -> None:
|
||
"""When no TibberPrice exists with starts_at ≤ t0, TibberPriceNotFoundError is raised."""
|
||
t0 = _ts(10, 0)
|
||
with Session(tibber_db) as session:
|
||
# Only a future price — starts_at > t0.
|
||
_insert_tibber_price(session, starts_at=_ts(10, 15), total=0.25)
|
||
session.commit()
|
||
|
||
fn = get_strategy("tibber")
|
||
with Session(tibber_db) as session:
|
||
deltas = PeriodDeltas(
|
||
d1=Decimal("1"), d2=Decimal("0"),
|
||
r1=Decimal("0"), r2=Decimal("0"),
|
||
)
|
||
with pytest.raises(TibberPriceNotFoundError):
|
||
fn(deltas, t0, self._VALUES, session)
|
||
|
||
def test_empty_tibber_table_raises(self, tibber_db) -> None:
|
||
"""Empty tibber_price table raises TibberPriceNotFoundError."""
|
||
fn = get_strategy("tibber")
|
||
with Session(tibber_db) as session:
|
||
deltas = PeriodDeltas(
|
||
d1=Decimal("1"), d2=Decimal("0"),
|
||
r1=Decimal("0"), r2=Decimal("0"),
|
||
)
|
||
with pytest.raises(TibberPriceNotFoundError):
|
||
fn(deltas, _ts(10), self._VALUES, session)
|
||
|
||
def test_pricing_snapshot_contains_expected_keys(self, tibber_db) -> None:
|
||
t0 = _ts(10, 0)
|
||
with Session(tibber_db) as session:
|
||
_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.20)
|
||
session.commit()
|
||
|
||
with Session(tibber_db) as session:
|
||
deltas = PeriodDeltas(
|
||
d1=Decimal("1"), d2=Decimal("0"),
|
||
r1=Decimal("0"), r2=Decimal("0"),
|
||
)
|
||
result = self._call(deltas, t0, session)
|
||
snapshot = result["pricing"]
|
||
assert snapshot["kind"] == "tibber"
|
||
assert "tibber_price_starts_at" in snapshot
|
||
assert "buy" in snapshot
|
||
assert "sell" in snapshot
|
||
|
||
def test_result_values_are_decimal_type(self, tibber_db) -> None:
|
||
t0 = _ts(10, 0)
|
||
with Session(tibber_db) as session:
|
||
_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.20)
|
||
session.commit()
|
||
|
||
with Session(tibber_db) as session:
|
||
deltas = PeriodDeltas(
|
||
d1=Decimal("1"), d2=Decimal("1"),
|
||
r1=Decimal("1"), r2=Decimal("1"),
|
||
)
|
||
result = self._call(deltas, t0, session)
|
||
assert isinstance(result["import_cost"], Decimal)
|
||
assert isinstance(result["export_revenue"], Decimal)
|
||
assert isinstance(result["net_cost"], Decimal)
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# Tibber precision test
|
||
# ---------------------------------------------------------------------------
|
||
|
||
|
||
class TestTibberDecimalPrecision:
|
||
"""Ensure Tibber arithmetic is exact Decimal (no float leakage)."""
|
||
|
||
def test_no_float_rounding_for_tricky_values(self, tibber_db) -> None:
|
||
"""total=0.1, energy_tax=0.2 — float gives 0.1+0.2 error; Decimal must be exact."""
|
||
t0 = _ts(10, 0)
|
||
with Session(tibber_db) as session:
|
||
_insert_tibber_price(session, starts_at=_ts(9, 45), total=0.3)
|
||
session.commit()
|
||
|
||
values = {
|
||
"energy": {"energy_tax": 0.1, "sell_adjust": 0.2},
|
||
"standing": {"management_fee": 5.99, "network_fee": 9.87},
|
||
"credits": {"heffingskorting": 600.0},
|
||
}
|
||
fn = get_strategy("tibber")
|
||
with Session(tibber_db) as session:
|
||
deltas = PeriodDeltas(
|
||
d1=Decimal("0"), d2=Decimal("0"),
|
||
r1=Decimal("1"), r2=Decimal("0"),
|
||
)
|
||
result = fn(deltas, t0, values, session)
|
||
# sell = 0.3 - 0.1 - 0.2 = 0.0 exactly (float gives ~2.8e-17)
|
||
assert result["export_revenue"] == Decimal("0"), (
|
||
f"Expected Decimal('0'), got {result['export_revenue']!r} — "
|
||
"float arithmetic leaking in?"
|
||
)
|