Files
EOS/tests/test_predictionabc.py
T
1abdd345c4 fix: unify mypy environments for local checks and CI (#1291)
The isolated pre-commit mypy hook previously omitted runtime type information that
make mypy used, hiding errors involving dependencies such as Pydantic and Pendulum.
Makefile, pre-commit and CI now run the same full-project typing policy in the
development environment defined by uv.lock.

- Use uv run --locked --exact --extra dev and the same mypy arguments for Makefile
  and the local hook. Check all of src and tests, including on configuration-only
  changes.
- Pin Python 3.13 for local development and the pre-commit CI job, and install the
  locked pre-commit version in CI.
- Disable incremental analysis because existing Pendulum cache state changes mypy 2.3.1
  diagnostics. Document the policy, the performance tradeoff and the existing typing debt.
- Add a regression test that exercises Makefile, the hook and the CI command in a
  temporary project, accepting valid dependency types and detecting deliberate
  Pydantic/Pendulum assignment errors.

Resolve the newly detected mypy diagnostics.

- Enable the numpydantic and Pydantic mypy plugins, retaining strict Pydantic
  constructor typing with init_typed = true. Validate raw/coercible payloads through model_validate.
- Propagate concrete record, provider and time-window types through generic collections,
  factories and lookup methods. Preserve runtime field inspection and generated time-window
  documentation.
- Align Pendulum annotations with actual factory/arithmetic results while retaining Pydantic
  validation adapters at runtime. Correct optional values, array boundaries, REST handlers
  and plotting interfaces.
- Add pinned scipy-stubs and types-psutil, update uv.lock, and supply the plugins' dependencies.
- Add runtime regression coverage for validated path defaults, normalized time-series metadata,
  generic field inspection, invalid timestamps and unsupported provider imports.

Runtime and compatibility details:

- Validate path defaults as Path objects while retaining raw string defaults needed by
  migration serialization with exclude_defaults.
- Normalize feed-in tariff lists and default charge rates to NumPy arrays; reject missing
  timestamps/uninitialized values explicitly. Importing into a provider without import support
  returns HTTP 400.
- Public JSON schemas and OpenAPI structure match main (excluding the generated version).

Signed-off-by: dr-dimitry

Signed-off-by: dr-dimitry
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: dr-dimitri <87113560+dr-dimitri@users.noreply.github.com>
Co-authored-by: Normann <github@koldrack.com>
2026-09-10 23:20:35 +02:00

407 lines
16 KiB
Python

import os
from datetime import datetime
from typing import Any, ClassVar, List, Optional, Union
import pandas as pd
import pendulum
import pytest
import pytest_asyncio
from pydantic import Field
from akkudoktoreos.core.coreabc import get_ems
from akkudoktoreos.prediction.prediction import PredictionCommonSettings
from akkudoktoreos.prediction.predictionabc import (
PredictionABC,
PredictionContainer,
PredictionProvider,
PredictionRecord,
PredictionSequence,
)
from akkudoktoreos.utils.datetimeutil import compare_datetimes, to_datetime, to_duration
# Derived classes for testing
# ---------------------------
class DerivedConfig(PredictionCommonSettings):
env_var: Optional[int] = Field(default=None, description="Test config by environment var")
instance_field: Optional[str] = Field(default=None, description="Test config by instance field")
class_constant: Optional[int] = Field(default=None, description="Test config by class constant")
class DerivedBase(PredictionABC):
instance_field: Optional[str] = Field(default=None, description="Field Value")
class_constant: ClassVar[int] = 30
class DerivedRecord(PredictionRecord):
prediction_value: Optional[float] = Field(default=None, description="Prediction Value")
class DerivedSequence(PredictionSequence[DerivedRecord]):
# overload
records: List[DerivedRecord] = Field(
default_factory=list, description="List of DerivedRecord records"
)
@classmethod
def record_class(cls) -> Any:
return DerivedRecord
class DerivedPredictionProvider(PredictionProvider[DerivedRecord]):
"""A concrete subclass of PredictionProvider for testing purposes."""
# overload
records: List[DerivedRecord] = Field(
default_factory=list, description="List of DerivedRecord records"
)
provider_enabled: ClassVar[bool] = False
provider_updated: ClassVar[bool] = False
@classmethod
def record_class(cls) -> Any:
return DerivedRecord
# Implement abstract methods for test purposes
def provider_id(self) -> str:
return "DerivedPredictionProvider"
def enabled(self) -> bool:
return self.provider_enabled
async def _update_data(self, force_update: Optional[bool] = False) -> None:
# Simulate update logic
DerivedPredictionProvider.provider_updated = True
class DerivedPredictionContainer(PredictionContainer):
providers: List[Union[DerivedPredictionProvider, PredictionProvider]] = Field(
default_factory=list, description="List of prediction providers"
)
# Tests
# ----------
class TestPredictionABC:
@pytest.fixture
def base(self, monkeypatch):
# Provide default values for configuration
monkeypatch.setenv("EOS_PREDICTION__HOURS", "10")
derived = DerivedBase()
derived.config.reset_settings()
assert derived.config.prediction.hours == 10
return derived
def test_config_value_from_env_variable(self, base, monkeypatch):
# From Prediction Config
monkeypatch.setenv("EOS_PREDICTION__HOURS", "2")
base.config.reset_settings()
assert base.config.prediction.hours == 2
def test_config_value_from_field_default(self, base, monkeypatch):
assert base.config.prediction.__class__.model_fields["historic_hours"].default == 48
assert base.config.prediction.historic_hours == 48
monkeypatch.setenv("EOS_PREDICTION__HISTORIC_HOURS", "128")
base.config.reset_settings()
assert base.config.prediction.historic_hours == 128
monkeypatch.delenv("EOS_PREDICTION__HISTORIC_HOURS")
base.config.reset_settings()
assert base.config.prediction.historic_hours == 48
def test_get_config_value_key_error(self, base):
with pytest.raises(AttributeError):
base.config.prediction.non_existent_key
# TestPredictionRecord fully covered by TestDataRecord
# ----------------------------------------------------
# TestPredictionSequence fully covered by TestDataSequence
# --------------------------------------------------------
# TestPredictionStartEndKeepMixin fully covered by TestPredictionContainer
# --------------------------------------------------------
@pytest.mark.asyncio
class TestPredictionProvider:
# Fixtures and helper functions
@pytest.fixture
def provider(self):
"""Fixture to provide an instance of TestPredictionProvider for testing."""
DerivedPredictionProvider.provider_enabled = True
DerivedPredictionProvider.provider_updated = False
return DerivedPredictionProvider()
@pytest.fixture
def sample_start_datetime(self):
"""Fixture for a sample start datetime."""
return to_datetime(datetime(2024, 11, 1, 12, 0))
def create_test_record(self, date, value):
"""Helper function to create a test PredictionRecord."""
return DerivedRecord(date_time=date, prediction_value=value)
# Tests
async def test_singleton_behavior(self, provider):
"""Test that PredictionProvider enforces singleton behavior."""
instance1 = provider
instance2 = DerivedPredictionProvider()
assert instance1 is instance2, (
"Singleton pattern is not enforced; instances are not the same."
)
async def test_update_computed_fields(self, provider, sample_start_datetime):
"""Test that computed fields `end_datetime` and `keep_datetime` are correctly calculated."""
ems_eos = get_ems()
ems_eos.set_start_datetime(sample_start_datetime)
provider.config.prediction.hours = 24 # 24 hours into the future
provider.config.prediction.historic_hours = 48 # 48 hours into the past
expected_end_datetime = sample_start_datetime + to_duration(
provider.config.prediction.hours * 3600
)
expected_keep_datetime = sample_start_datetime - to_duration(
provider.config.prediction.historic_hours * 3600
)
assert provider.end_datetime == expected_end_datetime, (
"End datetime is not calculated correctly."
)
assert provider.keep_datetime == expected_keep_datetime, (
"Keep datetime is not calculated correctly."
)
async def test_update_method_with_defaults(
self, provider, sample_start_datetime, config_eos, monkeypatch
):
"""Test the `update` method with default parameters."""
# EOS config supersedes
ems_eos = get_ems()
# The following values are currently not set in EOS config, we can override
monkeypatch.setenv("EOS_PREDICTION__HISTORIC_HOURS", "2")
assert os.getenv("EOS_PREDICTION__HISTORIC_HOURS") == "2"
provider.config.reset_settings()
ems_eos.set_start_datetime(sample_start_datetime)
await provider.update_data()
assert provider.config.prediction.hours == config_eos.prediction.hours
assert provider.config.prediction.historic_hours == 2
assert provider.ems_start_datetime == sample_start_datetime
assert provider.end_datetime == sample_start_datetime + to_duration(
f"{provider.config.prediction.hours} hours"
)
assert provider.keep_datetime == sample_start_datetime - to_duration("2 hours")
async def test_update_method_force_enable(self, provider, monkeypatch):
"""Test that `update` executes when `force_enable` is True, even if `enabled` is False."""
# Preset values that are needed by update
monkeypatch.setenv("EOS_GENERAL__LATITUDE", "37.7749")
monkeypatch.setenv("EOS_GENERAL__LONGITUDE", "-122.4194")
# Override enabled to return False for this test
DerivedPredictionProvider.provider_enabled = False
DerivedPredictionProvider.provider_updated = False
await provider.update_data(force_enable=True)
assert provider.enabled() is False, "Provider should be disabled, but enabled() is True."
assert DerivedPredictionProvider.provider_updated is True, (
"Provider should have been executed, but was not."
)
async def test_delete_by_datetime(self, provider, sample_start_datetime):
"""Test `delete_by_datetime` method for removing records by datetime range."""
# Add records to the provider for deletion testing
records = [
self.create_test_record(sample_start_datetime - to_duration("3 hours"), 1),
self.create_test_record(sample_start_datetime - to_duration("1 hour"), 2),
self.create_test_record(sample_start_datetime + to_duration("1 hour"), 3),
]
for record in records:
await provider.insert_by_datetime(record)
await provider.delete_by_datetime(
start_datetime=sample_start_datetime - to_duration("2 hours"),
end_datetime=sample_start_datetime + to_duration("2 hours"),
)
assert len(provider) == 1, (
"Only one record should remain after deletion by datetime."
)
assert provider.records[0].date_time == sample_start_datetime - to_duration("3 hours"), (
"Unexpected record remains."
)
@pytest.mark.asyncio
class TestPredictionContainer:
# Fixture and helpers
@pytest.fixture
def container(self):
container = DerivedPredictionContainer()
return container
@pytest_asyncio.fixture
async def container_with_providers(self):
records = [
# Test records - include 'prediction_value' key
self.create_test_record(datetime(2023, 11, 5), 1),
self.create_test_record(datetime(2023, 11, 6), 2),
self.create_test_record(datetime(2023, 11, 7), 3),
]
provider = DerivedPredictionProvider()
await provider.delete_by_datetime(start_datetime=None, end_datetime=None)
assert len(provider) == 0
for record in records:
await provider.insert_by_datetime(record)
assert len(provider) == 3
container = DerivedPredictionContainer()
container.providers.clear()
assert len(container.providers) == 0
container.providers.append(provider)
assert len(container.providers) == 1
return container
def create_test_record(self, date, value):
"""Helper function to create a test PredictionRecord."""
return DerivedRecord(date_time=date, prediction_value=value)
# Tests
@pytest.mark.parametrize(
"start, hours, end",
[
("2024-11-10 00:00:00", 24, "2024-11-11 00:00:00"), # No DST in Germany
("2024-08-10 00:00:00", 24, "2024-08-11 00:00:00"), # DST in Germany
("2024-03-31 00:00:00", 24, "2024-04-01 00:00:00"), # DST change (23 hours/ day)
("2024-10-27 00:00:00", 24, "2024-10-28 00:00:00"), # DST change (25 hours/ day)
("2024-11-10 00:00:00", 48, "2024-11-12 00:00:00"), # No DST in Germany
("2024-08-10 00:00:00", 48, "2024-08-12 00:00:00"), # DST in Germany
("2024-03-31 00:00:00", 48, "2024-04-02 00:00:00"), # DST change (47 hours/ day)
("2024-10-27 00:00:00", 48, "2024-10-29 00:00:00"), # DST change (49 hours/ day)
],
)
async def test_end_datetime(self, container, start, hours, end):
"""Test end datetime calculation from start datetime."""
ems_eos = get_ems()
ems_eos.set_start_datetime(to_datetime(start, in_timezone="Europe/Berlin"))
settings = {
"prediction": {
"hours": hours,
}
}
container.config.merge_settings_from_dict(settings)
expected = to_datetime(end, in_timezone="Europe/Berlin")
assert compare_datetimes(container.end_datetime, expected).equal
@pytest.mark.parametrize(
"start, historic_hours, expected_keep",
[
# Standard case
(
pendulum.datetime(2024, 8, 10, 0, 0, tz="Europe/Berlin"),
24,
pendulum.datetime(2024, 8, 9, 0, 0, tz="Europe/Berlin"),
),
# With DST, but should not affect historical data
(
pendulum.datetime(2024, 4, 1, 0, 0, tz="Europe/Berlin"),
24,
pendulum.datetime(2024, 3, 30, 23, 0, tz="Europe/Berlin"),
),
],
)
async def test_keep_datetime(self, container, start, historic_hours, expected_keep):
"""Test the `keep_datetime` property."""
ems_eos = get_ems()
ems_eos.set_start_datetime(to_datetime(start, in_timezone="Europe/Berlin"))
settings = {
"prediction": {
"historic_hours": historic_hours,
}
}
container.config.merge_settings_from_dict(settings)
expected = to_datetime(expected_keep, in_timezone="Europe/Berlin")
assert compare_datetimes(container.keep_datetime, expected).equal
@pytest.mark.parametrize(
"start, hours, expected_hours",
[
("2024-11-10 00:00:00", 24, 24), # No DST in Germany
("2024-08-10 00:00:00", 24, 24), # DST in Germany
("2024-03-31 00:00:00", 24, 23), # DST change in Germany (23 hours/ day)
("2024-10-27 00:00:00", 24, 25), # DST change in Germany (25 hours/ day)
],
)
async def test_total_hours(self, container, start, hours, expected_hours):
"""Test the `total_hours` property."""
ems_eos = get_ems()
ems_eos.set_start_datetime(to_datetime(start, in_timezone="Europe/Berlin"))
settings = {
"prediction": {
"hours": hours,
}
}
container.config.merge_settings_from_dict(settings)
assert container.total_hours == expected_hours
@pytest.mark.parametrize(
"start, historic_hours, expected_hours",
[
("2024-11-10 00:00:00", 24, 24), # No DST in Germany
("2024-08-10 00:00:00", 24, 24), # DST in Germany
("2024-04-01 00:00:00", 24, 24), # DST change on 2024-03-31 in Germany (23 hours/ day)
("2024-10-28 00:00:00", 24, 24), # DST change on 2024-10-27 in Germany (25 hours/ day)
],
)
async def test_keep_hours(self, container, start, historic_hours, expected_hours):
"""Test the `keep_hours` property."""
ems_eos = get_ems()
ems_eos.set_start_datetime(to_datetime(start, in_timezone="Europe/Berlin"))
settings = {
"prediction": {
"historic_hours": historic_hours,
}
}
container.config.merge_settings_from_dict(settings)
assert container.keep_hours == expected_hours
async def test_append_provider(self, container):
assert len(container.providers) == 0
container.providers.append(DerivedPredictionProvider())
assert len(container.providers) == 1
assert isinstance(container.providers[0], DerivedPredictionProvider)
@pytest.mark.skip(reason="type check not implemented")
async def test_append_provider_invalid_type(self, container):
with pytest.raises(ValueError, match="must be an instance of PredictionProvider"):
container.providers.append("not_a_provider")
async def test_len(self, container_with_providers):
assert len(container_with_providers) == 2
async def test_repr(self, container_with_providers):
representation = repr(container_with_providers)
assert representation.startswith("DerivedPredictionContainer(")
assert "DerivedPredictionProvider" in representation
async def test_to_json(self, container_with_providers):
json_str = container_with_providers.to_json()
container_other = DerivedPredictionContainer.from_json(json_str)
assert container_other == container_with_providers
async def test_from_json(self, container_with_providers):
json_str = container_with_providers.to_json()
container = DerivedPredictionContainer.from_json(json_str)
assert isinstance(container, DerivedPredictionContainer)
assert len(container.providers) == 1
assert container.providers[0] == container_with_providers.providers[0]
async def test_provider_by_id(self, container_with_providers):
provider = container_with_providers.provider_by_id("DerivedPredictionProvider")
assert isinstance(provider, DerivedPredictionProvider)