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Add new provider class for electricity fees providers. Add the generic providers: - ElecFeeFixed - ElecFeeImport The providers provide predictions for: - elecfee_consumption_amt_wh: Total fixed fee for consumed energy per Wh [amount/Wh]. This is the accumulation of all fixed per-Wh fees payable on "consumed energy - such as network charge, concession fee, and electricity charge - into a single amount. - elecfee_consumption_percent_amt: Total fixed surcharge on consumed energy, given as a percentage of the monetary amount already charged for that energy [%]. This is the accumulation of all percentage-based surcharges payable on top of the consumed-energy fee - such as VAT - into a single percentage. This is a percentage of the fee amount, not a per-Wh rate. - elecfee_feedin_amt_wh: Total fixed deduction from feed-in energy per Wh [amount/Wh]. This is the accumulation of all fixed per-Wh charges deducted from feed-in energy - such as metering fees or grid-operator handling "charges - into a single amount. Applied after the percentage-based deduction, i.e. it reduces the price by a flat amount per Wh rather than by a share of the raw price. - elecfee_feedin_percent_amt: Total percentage deducted from the raw feed-in price (spot price) [%]. This is the accumulation of all percentage-based deductions payable on the feed-in tariff - such as a marketing or balancing fee retained by the aggregator - into a single percentage. It is applied as `raw_price * (100 - percent) / 100`, i.e. it scales down the raw price rather than adding a surcharge to it. A new _apply_fee() method is added to the base class for ElecPrice and FeedInTariff to be used to add the fees in a consistent way. Fees are taken from the active ElecFee provider and applied to the raw prices given to the _apply_fee() method. The optional application of fees is added to: - ElecPriceAkkudoktor - ElecPriceFixed - ElecPriceEnergyCharts - ElecPriceSMARD - FeedInTariffEnergyCharts - FeedInTariffFixed - FeedInTariffSMARD The import providers ElecPriceImport and FeedInTariffImport do not apply fees by intentention. The following providers currently do not handle fees defined by ElecFee: - ElecPriceTibber - FeedInTariffAkkudoktor - FeedInTariffDvhubOnline - FeedInTariffTibber The tests for this feature are either added or existing tests are extended. The documentation was extended for the electricity fee provider settings. Besides this feature further improvements are added: * feat: add SMARD quarter-hour electricty price and feed-in tariff provider * feat: to_series method for TimeWindows and ValueTimeWindows Additional to to_array the time window sequence can now also produce a pandas series. Test have been extended to cover the series generation. * feat: use time windows in fixed feedin tariff provider Feedin tariff can now be configured by time windows - not a single value. * feat: EOSdash select for PVLib inverters and modules Provide PVLib inverter and module names in config selection. * feat: EOSdash lazy select for big option sets Add a new form for lazy selection of big option sets. Filtering and generation of the option set is done server-side. * fix: use raw data for ETS/ median prediction Use to raw time series data for ETS/ median prediction to avoid interference by e.g. dynamic grid charges. * fix: EOSdash config drops by type only on details resolve Drop configuration by type and path. Prevents dropping of configuration items with same type and level but different path. * fix: EOSdash configuration section closes on update Open section if searching or if last update touched this category — including updates on deeply nested sub-fields. * chore: make elecfeefixed, elecpricefixed and feedintarifffixed warn about no windows and default to 0 Missining configuration creates default 0 value and a warning instead of an exception. * fix: test setup for providers Reset db state on each test run. * chore: improve config option naming for elecpricefixed. * chore: adapt elecpricefixed test to changed time_windows naming * chore: factorized common price provider helpers to priceabc.py Factorized common price provider helpers to priceabc.py. Add tests for these helpers. Reduce/ change testing of elecpriceabc.py and feedintariffabc.py to cover only specifics. Rest of testing is already covered by test_priceabc.py. * chore: update version Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
240 lines
8.4 KiB
Python
240 lines
8.4 KiB
Python
import asyncio
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import json
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from pathlib import Path
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from unittest.mock import Mock, patch
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import numpy as np
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import pytest
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import requests
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from loguru import logger
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from akkudoktoreos.core.cache import CacheFileStore
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from akkudoktoreos.core.coreabc import get_ems
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from akkudoktoreos.prediction.elecpriceakkudoktor import (
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AkkudoktorElecPrice,
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AkkudoktorElecPriceValue,
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ElecPriceAkkudoktor,
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)
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from akkudoktoreos.utils.datetimeutil import to_datetime
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DIR_TESTDATA = Path(__file__).absolute().parent.joinpath("testdata")
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FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON = DIR_TESTDATA.joinpath(
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"elecpriceforecast_akkudoktor_1.json"
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)
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@pytest.fixture
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def provider(config_eos):
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"""Fixture to create a ElecPriceProvider instance."""
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config_eos.merge_settings_from_dict(
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{
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"elecprice": {
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"provider": "ElecPriceAkkudoktor",
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},
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}
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)
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provider = ElecPriceAkkudoktor()
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provider.highest_orig_datetime = None
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assert provider.enabled()
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provider._db_reset_state()
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return provider
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@pytest.fixture
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def sample_akkudoktor_1_json():
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"""Fixture that returns sample forecast data report."""
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with FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON.open(
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"r", encoding="utf-8", newline=None
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) as f_res:
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input_data = json.load(f_res)
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return input_data
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@pytest.fixture
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def cache_store():
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"""A pytest fixture that creates a new CacheFileStore instance for testing."""
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return CacheFileStore()
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class TestElecPriceAkkudokor:
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# ------------------------------------------------
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# General forecast
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# ------------------------------------------------
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def test_singleton_instance(self, provider):
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"""Test that ElecPriceForecast behaves as a singleton."""
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another_instance = ElecPriceAkkudoktor()
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assert provider is another_instance
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def test_invalid_provider(self, provider, monkeypatch):
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"""Test requesting an unsupported provider."""
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monkeypatch.setenv("EOS_ELECPRICE__ELECPRICE_PROVIDER", "<invalid>")
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provider.config.reset_settings()
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assert not provider.enabled()
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# ------------------------------------------------
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# Akkudoktor
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# ------------------------------------------------
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@patch("akkudoktoreos.prediction.elecpriceakkudoktor.logger.error")
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def test_validate_data_invalid_format(self, mock_logger, provider):
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"""Test validation for invalid Akkudoktor data."""
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invalid_data = '{"invalid": "data"}'
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with pytest.raises(ValueError):
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provider._validate_data(invalid_data)
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mock_logger.assert_called_once_with(mock_logger.call_args[0][0])
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@patch("requests.get")
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def test_request_forecast(self, mock_get, provider, sample_akkudoktor_1_json):
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"""Test requesting forecast from Akkudoktor."""
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# Mock response object
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mock_response = Mock()
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mock_response.status_code = 200
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mock_response.content = json.dumps(sample_akkudoktor_1_json)
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mock_get.return_value = mock_response
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# Test function
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akkudoktor_data = provider._request_forecast()
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assert isinstance(akkudoktor_data, AkkudoktorElecPrice)
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assert akkudoktor_data.values[0].model_dump() == AkkudoktorElecPriceValue(
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start_timestamp=1733785200000,
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end_timestamp=1733788800000,
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start="2024-12-09T23:00:00.000Z",
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end="2024-12-10T00:00:00.000Z",
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marketprice=92.85,
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unit="Eur/MWh",
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marketpriceEurocentPerKWh=9.29,
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).model_dump()
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@pytest.mark.asyncio
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@patch("requests.get")
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async def test_update_data(self, mock_get, provider, sample_akkudoktor_1_json, cache_store):
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"""Test fetching forecast from Akkudoktor."""
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# Mock response object
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mock_response = Mock()
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mock_response.status_code = 200
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mock_response.content = json.dumps(sample_akkudoktor_1_json)
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mock_get.return_value = mock_response
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cache_store.clear(clear_all=True)
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# Call the method
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ems_eos = get_ems()
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ems_eos.set_start_datetime(to_datetime("2024-12-11 00:00:00", in_timezone="Europe/Berlin"))
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await provider.update_data(force_enable=True, force_update=True)
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# Assert: Verify the result is as expected
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mock_get.assert_called_once()
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assert (
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len(provider) == 73
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) # we have 48 datasets in the api response, we want to know 48h into the future. The data we get has already 23h into the future so we need only 25h more. 48+25=73
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# Assert we get hours price values by resampling
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np_price_array = await provider.key_to_array(
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key="elecprice_marketprice_wh",
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start_datetime=provider.ems_start_datetime,
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end_datetime=provider.end_datetime,
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fill_method="ffill",
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)
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assert len(np_price_array) == provider.total_hours
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# with open(FILE_TESTDATA_ELECPRICEAKKUDOKTOR_2_JSON, "w") as f_out:
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# f_out.write(provider.to_json())
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@pytest.mark.asyncio
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@patch("requests.get")
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async def test_update_data_with_incomplete_forecast(self, mock_get, provider):
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"""Test `_update_data` with incomplete or missing forecast data."""
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incomplete_data: dict = {"meta": {}, "values": []}
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mock_response = Mock()
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mock_response.status_code = 200
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mock_response.content = json.dumps(incomplete_data)
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mock_get.return_value = mock_response
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logger.info("The following errors are intentional and part of the test.")
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with pytest.raises(ValueError):
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await provider._update_data(force_update=True)
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@pytest.mark.parametrize(
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"status_code, exception",
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[(400, requests.exceptions.HTTPError), (500, requests.exceptions.HTTPError), (200, None)],
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)
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@patch("requests.get")
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def test_request_forecast_status_codes(
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self, mock_get, provider, sample_akkudoktor_1_json, status_code, exception
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):
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"""Test handling of various API status codes."""
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mock_response = Mock()
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mock_response.status_code = status_code
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mock_response.content = json.dumps(sample_akkudoktor_1_json)
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mock_response.raise_for_status.side_effect = (
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requests.exceptions.HTTPError if exception else None
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)
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mock_get.return_value = mock_response
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if exception:
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with pytest.raises(exception):
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provider._request_forecast()
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else:
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provider._request_forecast()
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@pytest.mark.asyncio
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@patch("requests.get")
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@patch("akkudoktoreos.core.cache.CacheFileStore")
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async def test_cache_integration(self, mock_cache, mock_get, provider, sample_akkudoktor_1_json):
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"""Test caching of 8-day electricity price data."""
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# Mock response object
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mock_response = Mock()
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mock_response.status_code = 200
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mock_response.content = json.dumps(sample_akkudoktor_1_json)
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mock_get.return_value = mock_response
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# Mock cache object
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mock_cache_instance = mock_cache.return_value
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mock_cache_instance.get.return_value = None # Simulate no cache
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await provider._update_data(force_update=True)
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mock_cache_instance.create.assert_called_once()
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mock_cache_instance.get.assert_called_once()
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@pytest.mark.asyncio
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async def test_key_to_array_resampling(self, provider):
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"""Test resampling of forecast data to NumPy array."""
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await provider.update_data(force_update=True)
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array = await provider.key_to_array(
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key="elecprice_marketprice_wh",
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start_datetime=provider.ems_start_datetime,
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end_datetime=provider.end_datetime,
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fill_method="ffill",
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)
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assert isinstance(array, np.ndarray)
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assert len(array) == provider.total_hours
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# ------------------------------------------------
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# Development Akkudoktor
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# ------------------------------------------------
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@pytest.mark.skip(reason="For development only")
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def test_akkudoktor_development_forecast_data(self, provider):
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"""Fetch data from real Akkudoktor server."""
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# Preset, as this is usually done by update_data()
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provider.ems_start_datetime = to_datetime("2024-10-26 00:00:00")
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akkudoktor_data = provider._request_forecast()
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with FILE_TESTDATA_ELECPRICEAKKUDOKTOR_1_JSON.open(
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"w", encoding="utf-8", newline="\n"
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) as f_out:
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json.dump(akkudoktor_data, f_out, indent=4)
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