From 3476ea660d2cee9379e179520ef6ad28f884e97e Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 18:46:28 +0100 Subject: [PATCH 01/13] :fire: Remove support for old tariffs and range download * Remove support for old PVPC tariffs (assertion error if downloading prices < 2021-06-01) * Remove `download_prices_for_range` sync method (and its async pair), leaving only the logic to access current prices (just for HA Core integration) * Make `tariff` and `websession` required arguments --- README.md | 10 +-- aiopvpc/__init__.py | 3 +- aiopvpc/const.py | 3 - aiopvpc/parser.py | 20 +----- aiopvpc/pvpc_data.py | 164 +++---------------------------------------- 5 files changed, 20 insertions(+), 180 deletions(-) diff --git a/README.md b/README.md index afcbaf7..3f4e97b 100644 --- a/README.md +++ b/README.md @@ -28,14 +28,14 @@ Install with `pip install aiopvpc` or clone it to run tests or anything else. ## Usage ```python +import aiohttp from datetime import datetime from aiopvpc import PVPCData -pvpc_handler = PVPCData(tariff="discrimination", zone_ceuta_melilla=False) - -start = datetime(2021, 5, 20, 22) -end = datetime(2021, 6, 7, 16) -prices_range: dict = await pvpc_handler.async_download_prices_for_range(start, end) +async with aiohttp.ClientSession() as session: + pvpc_handler = PVPCData(websession=session, tariff="2.0TD") + prices: dict = await pvpc_handler.async_update_prices(datetime.utcnow()) +print(prices) ``` Check [this example on a jupyter notebook](https://github.com/azogue/aiopvpc/blob/master/Notebooks/Download%20PVPC%20prices.ipynb), where the downloader is combined with pandas and matplotlib to plot the electricity prices. diff --git a/aiopvpc/__init__.py b/aiopvpc/__init__.py index 5891c92..1d8d8f0 100644 --- a/aiopvpc/__init__.py +++ b/aiopvpc/__init__.py @@ -1,4 +1,5 @@ """Simple aio library to download Spanish electricity hourly prices.""" -from .pvpc_data import DEFAULT_POWER_KW, PVPCData, TARIFFS +from .const import DEFAULT_POWER_KW, TARIFFS +from .pvpc_data import PVPCData __all__ = ("DEFAULT_POWER_KW", "PVPCData", "TARIFFS") diff --git a/aiopvpc/const.py b/aiopvpc/const.py index 0f1b908..409833a 100644 --- a/aiopvpc/const.py +++ b/aiopvpc/const.py @@ -13,14 +13,11 @@ # Tariffs as internal keys in esios API data TARIFF_20TD_IDS = ["PCB", "CYM"] -OLD_TARIFS_IDS = ["GEN", "NOC", "VHC"] # Tariff names used in HomeAssistant integration TARIFFS = ["2.0TD", "2.0TD (Ceuta/Melilla)"] -OLD_TARIFFS = ["normal", "discrimination", "electric_car"] TARIFF2ID = dict(zip(TARIFFS, TARIFF_20TD_IDS)) -OLD_TARIFF2ID = dict(zip(OLD_TARIFFS, OLD_TARIFS_IDS)) # Contracted power DEFAULT_POWER_KW = 3.3 diff --git a/aiopvpc/parser.py b/aiopvpc/parser.py index 3b1abab..c504e37 100644 --- a/aiopvpc/parser.py +++ b/aiopvpc/parser.py @@ -5,15 +5,13 @@ * Parser for the contents of the JSON files """ from datetime import datetime, timedelta -from typing import Any, Dict, Optional, Union +from typing import Any, Dict, Union from aiopvpc.const import PRICE_PRECISION, REFERENCE_TZ, UTC_TZ, zoneinfo def extract_pvpc_data( - data: Dict[str, Any], - key: Optional[str] = None, - tz: zoneinfo.ZoneInfo = REFERENCE_TZ, + data: Dict[str, Any], key: str, tz: zoneinfo.ZoneInfo = REFERENCE_TZ ) -> Union[Dict[datetime, float], Dict[datetime, Dict[str, float]]]: """Parse the contents of a daily PVPC json file.""" ts_init = datetime( @@ -24,19 +22,7 @@ def extract_pvpc_data( def _parse_tariff_val(value, prec=PRICE_PRECISION) -> float: return round(float(value.replace(",", ".")) / 1000.0, prec) - def _parse_val(value) -> float: - return float(value.replace(",", ".")) - - if key is not None: - return { - ts_init + timedelta(hours=i): _parse_tariff_val(values_hour[key]) - for i, values_hour in enumerate(data["PVPC"]) - } - return { - ts_init - + timedelta(hours=i): { - k: _parse_val(v) for k, v in values_hour.items() if k not in ("Dia", "Hora") - } + ts_init + timedelta(hours=i): _parse_tariff_val(values_hour[key]) for i, values_hour in enumerate(data["PVPC"]) } diff --git a/aiopvpc/pvpc_data.py b/aiopvpc/pvpc_data.py index 91c9724..679ef2f 100644 --- a/aiopvpc/pvpc_data.py +++ b/aiopvpc/pvpc_data.py @@ -10,8 +10,7 @@ from collections import deque from datetime import date, datetime, timedelta from random import random -from time import monotonic -from typing import Any, Dict, Iterable, List, Optional, Tuple, Union +from typing import Any, Dict, Optional, Union import aiohttp import async_timeout @@ -21,8 +20,6 @@ DATE_CHANGE_TO_20TD, DEFAULT_POWER_KW, DEFAULT_TIMEOUT, - OLD_TARIFF2ID, - OLD_TARIFFS, REFERENCE_TZ, TARIFF2ID, TARIFFS, @@ -77,8 +74,8 @@ class PVPCData: def __init__( self, - tariff: Optional[str] = None, - websession: Optional[aiohttp.ClientSession] = None, + websession: aiohttp.ClientSession, + tariff: str, local_timezone: Union[str, zoneinfo.ZoneInfo] = REFERENCE_TZ, zone_ceuta_melilla: bool = False, power: float = DEFAULT_POWER_KW, @@ -98,35 +95,17 @@ def __init__( "Accept": "application/json", } - self._with_initial_session = websession is not None self._local_timezone = zoneinfo.ZoneInfo(str(local_timezone)) self._current_prices: Dict[datetime, float] = {} self._power = power self._power_valley = power_valley self._zone_ceuta_melilla = zone_ceuta_melilla - if tariff is None: - self.tariff = self.tariff_old = None - _LOGGER.warning("Collecting detailed PVPC data for all tariffs") - elif tariff in OLD_TARIFFS: - self.tariff_old = tariff - self.tariff = TARIFFS[1] if zone_ceuta_melilla else TARIFFS[0] - else: - self.tariff_old = "discrimination" - self.tariff = tariff - if tariff not in TARIFFS: # pragma: no cover - _LOGGER.error( - "Unknown tariff '%s'. Should be one of %s, or, " - "if using it to retrieve old prices, one of %s", - tariff, - TARIFFS, - OLD_TARIFFS, - ) - self.tariff = TARIFFS[1] if zone_ceuta_melilla else TARIFFS[0] + if tariff not in TARIFFS: # pragma: no cover + _LOGGER.error("Unknown tariff '%s'. Should be one of %s", tariff, TARIFFS) + self.tariff = TARIFFS[1] if zone_ceuta_melilla else TARIFFS[0] - async def _api_get_prices( - self, url: str, tariff: Optional[str] - ) -> Dict[datetime, Any]: + async def _api_get_prices(self, url: str, tariff: str) -> Dict[datetime, Any]: assert self._session is not None resp = await self._session.get(url, headers=self._headers) if resp.status < 400: @@ -165,11 +144,9 @@ async def _download_pvpc_prices(self, day: date) -> Dict[datetime, Any]: Prices are referenced with datetimes in UTC. """ + assert day >= DATE_CHANGE_TO_20TD, "Deprecated support for old tariffs" url = URL_PVPC_RESOURCE.format(day=day) - if day < DATE_CHANGE_TO_20TD: - tariff = OLD_TARIFF2ID.get(self.tariff_old) if self.tariff_old else None - else: - tariff = TARIFF2ID.get(self.tariff) if self.tariff else None + tariff = TARIFF2ID[self.tariff] try: async with async_timeout.timeout(2 * self.timeout): @@ -277,10 +254,7 @@ def process_state_and_attributes(self, utc_now: datetime) -> bool: If not, it is converted to UTC from the original timezone, or set as UTC-time if it is a naive datetime. """ - tariff = self.tariff - if utc_now.isoformat() < DATE_CHANGE_TO_20TD.isoformat(): - tariff = self.tariff_old - attributes: Dict[str, Any] = {"attribution": ATTRIBUTION, "tariff": tariff} + attributes: Dict[str, Any] = {"attribution": ATTRIBUTION, "tariff": self.tariff} utc_time = ensure_utc_time(utc_now.replace(minute=0, second=0, microsecond=0)) actual_time = utc_time.astimezone(self._local_timezone) # todo power_period/power_price €/kW*año @@ -321,121 +295,3 @@ def process_state_and_attributes(self, utc_now: datetime) -> bool: ) self.attributes = {**attributes, **price_attrs} return True - - async def _download_worker(self, wk_name: str, queue: asyncio.Queue): - downloaded_prices = [] - try: - while True: - day: date = await queue.get() - tic = monotonic() - prices = await self._download_pvpc_prices(day) - took = monotonic() - tic - queue.task_done() - if not prices: - _LOGGER.warning( - "[%s]: Bad download for day: %s in %.3f s", wk_name, day, took - ) - continue - - downloaded_prices.append((day, prices)) - _LOGGER.debug( - "[%s]: Task done for day: %s in %.3f s", wk_name, day, took - ) - except asyncio.CancelledError: - return downloaded_prices - - async def _multi_download( - self, days_to_download: List[date], max_calls: int - ) -> Iterable[Tuple[date, Dict[datetime, Any]]]: - """Multiple requests using an asyncio.Queue for concurrency.""" - queue: asyncio.Queue = asyncio.Queue() - # setup `max_calls` queue workers - worker_tasks = [ - asyncio.create_task(self._download_worker(f"worker-{i+1}", queue)) - for i in range(max_calls) - ] - # fill queue - for day in days_to_download: - queue.put_nowait(day) - - # wait for the queue to process all - await queue.join() - - for task in worker_tasks: - task.cancel() - # Wait until all worker tasks are cancelled. - wk_tasks_results = await asyncio.gather(*worker_tasks, return_exceptions=True) - - return sorted( - (day_data for wk_results in wk_tasks_results for day_data in wk_results), - key=lambda x: x[0], - ) - - async def _ensure_session(self): - if self._session is None: - assert not self._with_initial_session - self._session = aiohttp.ClientSession() - - async def _close_temporal_session(self): - if not self._with_initial_session and self._session is not None: - await self._session.close() - self._session = None - - async def async_download_prices_for_range( - self, start: datetime, end: datetime, concurrency_calls: int = 20 - ) -> Dict[datetime, Any]: - """Download a time range burst of electricity prices from the ESIOS API.""" - - def _adjust_dates(ts: datetime) -> Tuple[datetime, datetime]: - # adjust dates and tz from inputs to retrieve prices as it was in - # Spain mainland, so tz-independent!! - ts_ref = datetime( - *ts.timetuple()[:6], tzinfo=self._local_timezone - ).astimezone(REFERENCE_TZ) - ts_utc = ts_ref.astimezone(UTC_TZ) - return ts_utc, ts_ref - - start_utc, start_local = _adjust_dates(start) - end_utc, end_local = _adjust_dates(end) - delta: timedelta = end_local.date() - start_local.date() - days_to_download = [ - start_local.date() + timedelta(days=i) for i in range(delta.days + 1) - ] - - tic = monotonic() - max_calls = concurrency_calls - await self._ensure_session() - data_days = await self._multi_download(days_to_download, max_calls) - await self._close_temporal_session() - - prices = { - hour: hourly_data[hour] - for (day, hourly_data) in data_days - for hour in hourly_data - if start_utc <= hour <= end_utc - } - if prices: - _LOGGER.warning( - "Download of %d prices from %s to %s in %.2f sec", - len(prices), - min(prices), - max(prices), - monotonic() - tic, - ) - else: - _LOGGER.error( - "BAD Download of PVPC prices from %s to %s in %.2f sec", - start, - end, - monotonic() - tic, - ) - - return prices - - def download_prices_for_range( - self, start: datetime, end: datetime, concurrency_calls: int = 20 - ) -> Dict[datetime, Any]: - """Blocking method to download a time range burst of elec prices.""" - return asyncio.run( - self.async_download_prices_for_range(start, end, concurrency_calls) - ) From bf98d11f8a65ea66a5116443a7d34617af7f5114 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 18:48:26 +0100 Subject: [PATCH 02/13] :fire: Remove tests for range-download methods --- tests/test_pvpc.py | 76 +----------------------------------- tests/test_real_api_calls.py | 32 --------------- 2 files changed, 1 insertion(+), 107 deletions(-) diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index ba34c5a..d544285 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -2,12 +2,11 @@ import logging from asyncio import TimeoutError from datetime import datetime, timedelta -from unittest.mock import patch import pytest from aiohttp import ClientError -from aiopvpc.const import OLD_TARIFS_IDS, REFERENCE_TZ, UTC_TZ +from aiopvpc.const import REFERENCE_TZ, UTC_TZ from aiopvpc.pvpc_data import PVPCData from tests.conftest import MockAsyncSession, TZ_TEST @@ -106,79 +105,6 @@ async def test_bad_downloads( assert len(prices) == 0 -@pytest.mark.parametrize( - "timezone, start, end", - ( - ( - TZ_TEST, - datetime(2019, 10, 26, 15, tzinfo=TZ_TEST), - datetime(2019, 10, 27, 13, tzinfo=TZ_TEST), - ), - ( - REFERENCE_TZ, - datetime(2019, 10, 26, 15, tzinfo=REFERENCE_TZ), - datetime(2019, 10, 27, 13, tzinfo=REFERENCE_TZ), - ), - ), -) -def test_full_data_download_range(timezone, start, end): - """Test retrieval of full PVPC data in a day range.""" - with patch("aiohttp.ClientSession", MockAsyncSession): - pvpc_data = PVPCData(local_timezone=timezone) - prices = pvpc_data.download_prices_for_range(start, end) - - assert len(prices) == 24 - first_price = min(prices) - last_price = max(prices) - data_first_hour = prices[first_price] - - # Check full PVPC data is retrieved - assert len(data_first_hour) == 30 - assert all(tag in data_first_hour for tag in OLD_TARIFS_IDS) - - # Check units have not changed in full data retrieval (they are in €/MWh) - assert all(data_first_hour[tag] > 1 for tag in OLD_TARIFS_IDS) - - # check tz-alignment (price at 15h is tz-independent) - assert prices[first_price]["NOC"] == 119.16 - assert first_price.astimezone(timezone).hour == 15 - assert last_price.astimezone(timezone).hour == 13 - - -@pytest.mark.asyncio -async def test_download_range(caplog): - """Test retrieval of full PVPC data in a day range.""" - start = datetime(2019, 10, 26, 15) - end = datetime(2019, 10, 28, 13) - mock_session = MockAsyncSession() - - with caplog.at_level(logging.WARNING): - pvpc_data = PVPCData( - tariff="electric_car", local_timezone=TZ_TEST, websession=mock_session - ) - prices = await pvpc_data.async_download_prices_for_range(start, end) - assert mock_session.call_count == 3 - assert len(prices) == 34 - assert len(caplog.messages) == 2 - - no_prices = await pvpc_data.async_download_prices_for_range( - datetime(2010, 8, 27, tzinfo=TZ_TEST), - datetime(2010, 8, 27, 22, tzinfo=TZ_TEST), - ) - assert len(no_prices) == 0 - assert len(caplog.messages) == 4 - assert not await pvpc_data.async_download_prices_for_range( - datetime(2010, 8, 27), datetime(2010, 8, 27, 23) - ) - assert len(caplog.messages) == 7 - - first_price = min(prices) - assert first_price.hour == 14 and first_price.tzname() == "UTC" - # Check only tariff values are retrieved - assert isinstance(prices[first_price], float) - assert prices[first_price] < 1 - - async def _run_h_step( mock_session: MockAsyncSession, pvpc_data: PVPCData, start: datetime ): diff --git a/tests/test_real_api_calls.py b/tests/test_real_api_calls.py index a1e9224..9d5a231 100644 --- a/tests/test_real_api_calls.py +++ b/tests/test_real_api_calls.py @@ -7,38 +7,6 @@ from aiopvpc import PVPCData -@pytest.mark.real_api_call -def test_real_download_range(): - # No async - pvpc_handler = PVPCData("normal") - start = datetime(2019, 10, 26, 15) - end = datetime(2019, 10, 28, 13) - prices = pvpc_handler.download_prices_for_range(start, end) - assert len(prices) == 48 - - no_prices = pvpc_handler.download_prices_for_range( - datetime(2010, 8, 26, 23), datetime(2010, 8, 27, 22) - ) - assert len(no_prices) == 0 - - -@pytest.mark.real_api_call -@pytest.mark.asyncio -async def test_real_download_range_async(): - start = datetime(2019, 10, 26, 15) - end = datetime(2019, 10, 28, 13) - async with ClientSession() as session: - pvpc_handler = PVPCData("normal", websession=session) - prices = await pvpc_handler.async_download_prices_for_range(start, end) - assert len(prices) == 48 - - # without session also works, creating one for each download range call - pvpc_handler_no_s = PVPCData("normal") - prices2 = await pvpc_handler_no_s.async_download_prices_for_range(start, end) - assert len(prices2) == 48 - assert prices == prices2 - - @pytest.mark.real_api_call @pytest.mark.asyncio async def test_real_download_today_async(): From 1f35a23bc074c021a5f279be260d08cfb3decd04 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 18:51:04 +0100 Subject: [PATCH 03/13] :truck: Change test patterns to new tariffs by substituting old examples in DST days from 2019 to equivalent days since 2021-06, using the new tariff keys --- .../api_examples/PVPC_CURV_DD_2019_03_31.json | 786 ---------------- .../api_examples/PVPC_CURV_DD_2019_10_26.json | 820 ----------------- .../api_examples/PVPC_CURV_DD_2019_10_27.json | 854 ------------------ .../api_examples/PVPC_CURV_DD_2021_10_30.json | 604 +++++++++++++ .../api_examples/PVPC_CURV_DD_2021_10_31.json | 629 +++++++++++++ .../api_examples/PVPC_CURV_DD_2022_03_27.json | 579 ++++++++++++ tests/conftest.py | 12 +- tests/test_pvpc.py | 38 +- 8 files changed, 1837 insertions(+), 2485 deletions(-) delete mode 100644 tests/api_examples/PVPC_CURV_DD_2019_03_31.json delete mode 100644 tests/api_examples/PVPC_CURV_DD_2019_10_26.json delete mode 100644 tests/api_examples/PVPC_CURV_DD_2019_10_27.json create mode 100644 tests/api_examples/PVPC_CURV_DD_2021_10_30.json create mode 100644 tests/api_examples/PVPC_CURV_DD_2021_10_31.json create mode 100644 tests/api_examples/PVPC_CURV_DD_2022_03_27.json diff --git a/tests/api_examples/PVPC_CURV_DD_2019_03_31.json b/tests/api_examples/PVPC_CURV_DD_2019_03_31.json deleted file mode 100644 index a8e95ce..0000000 --- a/tests/api_examples/PVPC_CURV_DD_2019_03_31.json +++ /dev/null @@ -1,786 +0,0 @@ -{ - "PVPC": [ - { - "Dia": "31/03/2019", - "Hora": "00-01", - "GEN": "123,33", - "NOC": "73,28", - "VHC": "78,13", - "COFGEN": "0,000095032537000000", - "COFNOC": "0,000183477177000000", - "COFVHC": "0,000161590950000000", - "PMHGEN": "67,19", - "PMHNOC": "64,11", - "PMHVHC": "67,57", - "SAHGEN": "3,16", - "SAHNOC": "3,01", - "SAHVHC": "3,18", - "FOMGEN": "0,03", - "FOMNOC": "0,03", - "FOMVHC": "0,03", - "FOSGEN": "0,14", - "FOSNOC": "0,13", - "FOSVHC": "0,14", - "INTGEN": "0,85", - "INTNOC": "0,81", - "INTVHC": "0,85", - "PCAPGEN": "5,76", - "PCAPNOC": "0,96", - "PCAPVHC": "1,36", - "TEUGEN": "44,03", - "TEUNOC": "2,22", - "TEUVHC": "2,88", - "CCVGEN": "2,18", - "CCVNOC": "2,01", - "CCVVHC": "2,13" - }, - { - "Dia": "31/03/2019", - "Hora": "01-02", - "GEN": "121,74", - "NOC": "71,51", - "VHC": "67,73", - "COFGEN": "0,000078005387000000", - "COFNOC": "0,000167046535000000", - "COFVHC": "0,000165251194000000", - "PMHGEN": "65,15", - "PMHNOC": "62,00", - "PMHVHC": "59,98", - "SAHGEN": "3,53", - "SAHNOC": "3,35", - "SAHVHC": "3,25", - "FOMGEN": "0,03", - "FOMNOC": "0,03", - "FOMVHC": "0,03", - "FOSGEN": "0,14", - "FOSNOC": "0,13", - "FOSVHC": "0,13", - "INTGEN": "0,86", - "INTNOC": "0,81", - "INTVHC": "0,79", - "PCAPGEN": "5,83", - "PCAPNOC": "0,96", - "PCAPVHC": "0,75", - "TEUGEN": "44,03", - "TEUNOC": "2,22", - "TEUVHC": "0,89", - "CCVGEN": "2,17", - "CCVNOC": "1,99", - "CCVVHC": "1,93" - }, - { - "Dia": "31/03/2019", - "Hora": "03-04", - "GEN": "117,17", - "NOC": "67,10", - "VHC": "63,47", - "COFGEN": "0,000061743246000000", - "COFNOC": "0,000144796631000000", - "COFVHC": "0,000155660267000000", - "PMHGEN": "60,08", - "PMHNOC": "57,13", - "PMHVHC": "55,28", - "SAHGEN": "4,08", - "SAHNOC": "3,88", - "SAHVHC": "3,75", - "FOMGEN": "0,03", - "FOMNOC": "0,03", - "FOMVHC": "0,03", - "FOSGEN": "0,14", - "FOSNOC": "0,14", - "FOSVHC": "0,13", - "INTGEN": "0,86", - "INTNOC": "0,82", - "INTVHC": "0,79", - "PCAPGEN": "5,84", - "PCAPNOC": "0,97", - "PCAPVHC": "0,75", - "TEUGEN": "44,03", - "TEUNOC": "2,22", - "TEUVHC": "0,89", - "CCVGEN": "2,10", - "CCVNOC": "1,93", - "CCVVHC": "1,86" - }, - { - "Dia": "31/03/2019", - "Hora": "04-05", - "GEN": "116,26", - "NOC": "66,18", - "VHC": "62,59", - "COFGEN": "0,000058452382000000", - "COFNOC": "0,000139607570000000", - "COFVHC": "0,000148113871000000", - "PMHGEN": "59,00", - "PMHNOC": "56,06", - "PMHVHC": "54,24", - "SAHGEN": "4,25", - "SAHNOC": "4,04", - "SAHVHC": "3,91", - "FOMGEN": "0,03", - "FOMNOC": "0,03", - "FOMVHC": "0,03", - "FOSGEN": "0,14", - "FOSNOC": "0,14", - "FOSVHC": "0,13", - "INTGEN": "0,86", - "INTNOC": "0,82", - "INTVHC": "0,79", - "PCAPGEN": "5,86", - "PCAPNOC": "0,97", - "PCAPVHC": "0,75", - "TEUGEN": "44,03", - "TEUNOC": "2,22", - "TEUVHC": "0,89", - "CCVGEN": "2,09", - "CCVNOC": "1,92", - "CCVVHC": "1,85" - }, - { - "Dia": "31/03/2019", - "Hora": "05-06", - "GEN": "118,70", - "NOC": "68,50", - "VHC": "64,77", - "COFGEN": "0,000057634518000000", - "COFNOC": "0,000143269153000000", - "COFVHC": "0,000142076871000000", - "PMHGEN": "61,50", - "PMHNOC": "58,44", - "PMHVHC": "56,50", - "SAHGEN": "4,14", - "SAHNOC": "3,93", - "SAHVHC": "3,80", - "FOMGEN": "0,03", - "FOMNOC": "0,03", - "FOMVHC": "0,03", - "FOSGEN": "0,14", - "FOSNOC": "0,14", - "FOSVHC": "0,13", - "INTGEN": "0,86", - "INTNOC": "0,82", - "INTVHC": "0,79", - "PCAPGEN": "5,86", - "PCAPNOC": "0,97", - "PCAPVHC": "0,75", - "TEUGEN": "44,03", - "TEUNOC": "2,22", - "TEUVHC": "0,89", - "CCVGEN": "2,13", - "CCVNOC": "1,95", - "CCVVHC": "1,89" - }, - { - "Dia": "31/03/2019", - "Hora": "06-07", - "GEN": "120,24", - "NOC": "70,02", - "VHC": "66,25", - "COFGEN": 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"TEUCYM": "0,92", + "CCVPCB": "2,23", + "CCVCYM": "2,23", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "08-09", + "PCB": "88,03", + "CYM": "88,03", + "COF2TD": "0,000061629048000000", + "PMHPCB": "65,14", + "PMHCYM": "65,14", + "SAHPCB": "19,52", + "SAHCYM": "19,52", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,25", + "CCVCYM": "2,25", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "09-10", + "PCB": "81,82", + "CYM": "81,82", + "COF2TD": "0,000067518625000000", + "PMHPCB": "61,06", + "PMHCYM": "61,06", + "SAHPCB": "17,48", + "SAHCYM": "17,48", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,15", + "CCVCYM": "2,15", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "10-11", + "PCB": "102,63", + "CYM": "102,63", + "COF2TD": "0,000084869912000000", + "PMHPCB": "83,73", + "PMHCYM": "83,73", + "SAHPCB": "15,32", + "SAHCYM": "15,32", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,46", + "CCVCYM": "2,46", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "11-12", + "PCB": "91,09", + "CYM": "91,09", + "COF2TD": "0,000101734361000000", + "PMHPCB": "75,51", + "PMHCYM": "75,51", + "SAHPCB": "12,18", + "SAHCYM": "12,18", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,28", + "CCVCYM": "2,28", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "12-13", + "PCB": "91,10", + "CYM": "91,10", + "COF2TD": "0,000108754452000000", + "PMHPCB": "75,42", + "PMHCYM": "75,42", + "SAHPCB": "12,29", + "SAHCYM": "12,29", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,28", + "CCVCYM": "2,28", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "13-14", + "PCB": "86,49", + "CYM": "86,49", + "COF2TD": "0,000110386598000000", + "PMHPCB": "71,34", + "PMHCYM": "71,34", + "SAHPCB": "11,83", + "SAHCYM": "11,83", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,21", + "CCVCYM": "2,21", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "14-15", + "PCB": "79,78", + "CYM": "79,78", + "COF2TD": "0,000114934537000000", + "PMHPCB": "65,41", + "PMHCYM": "65,41", + "SAHPCB": "11,15", + "SAHCYM": "11,15", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,10", + "CCVCYM": "2,10", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "15-16", + "PCB": "80,80", + "CYM": "80,80", + "COF2TD": "0,000114142763000000", + "PMHPCB": "65,78", + "PMHCYM": "65,78", + "SAHPCB": "11,78", + "SAHCYM": "11,78", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,12", + "CCVCYM": "2,12", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "16-17", + "PCB": "81,34", + "CYM": "81,34", + "COF2TD": "0,000100989241000000", + "PMHPCB": "64,88", + "PMHCYM": "64,88", + "SAHPCB": "13,20", + "SAHCYM": "13,20", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,14", + "CCVCYM": "2,14", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "17-18", + "PCB": "92,09", + "CYM": "92,09", + "COF2TD": "0,000092132184000000", + "PMHPCB": "76,10", + "PMHCYM": "76,10", + "SAHPCB": "12,56", + "SAHCYM": "12,56", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,31", + "CCVCYM": "2,31", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "18-19", + "PCB": "111,30", + "CYM": "111,30", + "COF2TD": "0,000089664056000000", + "PMHPCB": "96,55", + "PMHCYM": "96,55", + "SAHPCB": "11,04", + "SAHCYM": "11,04", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,59", + "CCVCYM": "2,59", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "19-20", + "PCB": "122,85", + "CYM": "122,85", + "COF2TD": "0,000094482458000000", + "PMHPCB": "109,30", + "PMHCYM": "109,30", + "SAHPCB": "9,65", + "SAHCYM": "9,65", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,77", + "CCVCYM": "2,77", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "20-21", + "PCB": "131,87", + "CYM": "131,87", + "COF2TD": "0,000106522306000000", + "PMHPCB": "118,82", + "PMHCYM": "118,82", + "SAHPCB": "9,02", + "SAHCYM": "9,02", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "2,90", + "CCVCYM": "2,90", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "21-22", + "PCB": "185,38", + "CYM": "185,38", + "COF2TD": "0,000127469738000000", + "PMHPCB": "174,92", + "PMHCYM": "174,92", + "SAHPCB": "5,63", + "SAHCYM": "5,63", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "3,70", + "CCVCYM": "3,70", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "22-23", + "PCB": "165,54", + "CYM": "165,54", + "COF2TD": "0,000132668134000000", + "PMHPCB": "154,77", + "PMHCYM": "154,77", + "SAHPCB": "6,24", + "SAHCYM": "6,24", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "3,41", + "CCVCYM": "3,41", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + }, + { + "Dia": "27/03/2022", + "Hora": "23-24", + "PCB": "152,39", + "CYM": "152,39", + "COF2TD": "0,000119920791000000", + "PMHPCB": "140,35", + "PMHCYM": "140,35", + "SAHPCB": "7,71", + "SAHCYM": "7,71", + "FOMPCB": "0,03", + "FOMCYM": "0,03", + "FOSPCB": "0,17", + "FOSCYM": "0,17", + "INTPCB": "0,00", + "INTCYM": "0,00", + "PCAPPCB": "0,00", + "PCAPCYM": "0,00", + "TEUPCB": "0,92", + "TEUCYM": "0,92", + "CCVPCB": "3,22", + "CCVCYM": "3,22", + "EDSRPCB": "0,00", + "EDSRCYM": "0,00" + } + ] +} diff --git a/tests/conftest.py b/tests/conftest.py index 7b10957..49fddd8 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -12,9 +12,9 @@ TEST_EXAMPLES_PATH = pathlib.Path(__file__).parent / "api_examples" TZ_TEST = zoneinfo.ZoneInfo("Atlantic/Canary") -FIXTURE_JSON_DATA_2019_10_26 = "PVPC_CURV_DD_2019_10_26.json" -FIXTURE_JSON_DATA_2019_10_27 = "PVPC_CURV_DD_2019_10_27.json" -FIXTURE_JSON_DATA_2019_03_31 = "PVPC_CURV_DD_2019_03_31.json" +FIXTURE_JSON_DATA_2021_10_30 = "PVPC_CURV_DD_2021_10_30.json" +FIXTURE_JSON_DATA_2021_10_31 = "PVPC_CURV_DD_2021_10_31.json" +FIXTURE_JSON_DATA_2022_03_27 = "PVPC_CURV_DD_2022_03_27.json" FIXTURE_JSON_DATA_2021_06_01 = "PVPC_CURV_DD_2021_06_01.json" _DEFAULT_EMPTY_VALUE = {"message": "No values for specified archive"} @@ -47,9 +47,9 @@ def __init__(self, status=200, exc=None): self.exc = exc self.responses = { - date(2019, 3, 31): load_fixture(FIXTURE_JSON_DATA_2019_03_31), - date(2019, 10, 26): load_fixture(FIXTURE_JSON_DATA_2019_10_26), - date(2019, 10, 27): load_fixture(FIXTURE_JSON_DATA_2019_10_27), + date(2022, 3, 27): load_fixture(FIXTURE_JSON_DATA_2022_03_27), + date(2021, 10, 30): load_fixture(FIXTURE_JSON_DATA_2021_10_30), + date(2021, 10, 31): load_fixture(FIXTURE_JSON_DATA_2021_10_31), date(2021, 6, 1): load_fixture(FIXTURE_JSON_DATA_2021_06_01), } diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index d544285..55e61e9 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -14,17 +14,17 @@ @pytest.mark.parametrize( "day_str, timezone, zone_cm, num_prices, num_calls, num_prices_8h, available_8h", ( - ("2019-10-26 00:00:00+08:00", TZ_TEST, False, 0, 1, 0, False), - ("2019-10-26 00:00:00", TZ_TEST, False, 24, 1, 24, True), - ("2019-10-27 00:00:00", TZ_TEST, False, 25, 1, 25, True), - ("2019-03-31 20:00:00", TZ_TEST, False, 23, 2, 23, False), - ("2019-03-31 20:00:00+04:00", TZ_TEST, False, 23, 1, 23, False), - ("2019-10-26 21:00:00", TZ_TEST, False, 49, 2, 26, True), - ("2019-10-26 21:00:00+01:00", TZ_TEST, False, 49, 2, 26, True), - ("2019-10-26 00:00:00", REFERENCE_TZ, True, 24, 1, 24, True), - ("2019-10-27 00:00:00", REFERENCE_TZ, True, 25, 1, 25, True), - ("2019-03-31 20:00:00", REFERENCE_TZ, True, 23, 2, 23, False), - ("2019-10-26 21:00:00", REFERENCE_TZ, True, 49, 2, 25, True), + ("2021-10-30 00:00:00+08:00", TZ_TEST, False, 0, 1, 0, False), + ("2021-10-30 00:00:00", TZ_TEST, False, 24, 1, 24, True), + ("2021-10-31 00:00:00", TZ_TEST, False, 25, 1, 25, True), + ("2022-03-27 20:00:00", TZ_TEST, False, 23, 2, 23, False), + ("2022-03-27 20:00:00+04:00", TZ_TEST, False, 23, 1, 23, False), + ("2021-10-30 21:00:00", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 21:00:00+01:00", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 00:00:00", REFERENCE_TZ, True, 24, 1, 24, True), + ("2021-10-31 00:00:00", REFERENCE_TZ, True, 25, 1, 25, True), + ("2022-03-27 20:00:00", REFERENCE_TZ, True, 23, 2, 23, False), + ("2021-10-30 21:00:00", REFERENCE_TZ, True, 49, 2, 25, True), ("2021-06-01 09:00:00", REFERENCE_TZ, True, 24, 1, 24, True), ), ) @@ -91,9 +91,9 @@ async def test_bad_downloads( mock_session = MockAsyncSession(status=status, exc=exception) with caplog.at_level(logging.INFO): pvpc_data = PVPCData( - local_timezone=REFERENCE_TZ, - tariff="normal", websession=mock_session, + tariff="2.0TD", + local_timezone=REFERENCE_TZ, ) pvpc_data.source_available = available assert not pvpc_data.process_state_and_attributes(day) @@ -128,11 +128,11 @@ async def _run_h_step( @pytest.mark.asyncio async def test_reduced_api_download_rate(local_tz): """Test time evolution and number of API calls.""" - start = datetime(2019, 10, 26, 15, tzinfo=UTC_TZ) + start = datetime(2021, 10, 30, 15, tzinfo=UTC_TZ) mock_session = MockAsyncSession() # logging.critical(local_tz) pvpc_data = PVPCData( - tariff="electric_car", local_timezone=local_tz, websession=mock_session + websession=mock_session, tariff="2.0TD", local_timezone=local_tz ) # avoid extra calls at day if already got all today prices @@ -142,7 +142,7 @@ async def test_reduced_api_download_rate(local_tz): assert len(prices) == 24 # first call for next-day prices - assert start == datetime(2019, 10, 26, 18, tzinfo=UTC_TZ) + assert start == datetime(2021, 10, 30, 18, tzinfo=UTC_TZ) start, prices = await _run_h_step(mock_session, pvpc_data, start) assert mock_session.call_count == 2 assert len(prices) == 49 @@ -161,9 +161,9 @@ async def test_reduced_api_download_rate(local_tz): # assert len(prices) == 25 # call for next-day prices (no more available) - assert start == datetime(2019, 10, 27, 19, tzinfo=UTC_TZ) + assert start == datetime(2021, 10, 31, 19, tzinfo=UTC_TZ) call_count = mock_session.call_count - while start.astimezone(local_tz) <= datetime(2019, 10, 27, 23, tzinfo=local_tz): + while start.astimezone(local_tz) <= datetime(2021, 10, 31, 23, tzinfo=local_tz): start, prices = await _run_h_step(mock_session, pvpc_data, start) call_count += 1 assert mock_session.call_count == call_count @@ -172,7 +172,7 @@ async def test_reduced_api_download_rate(local_tz): # assert mock_session.call_count == 6 assert pvpc_data.state assert pvpc_data.state_available - assert start.astimezone(local_tz) == datetime(2019, 10, 28, tzinfo=local_tz) + assert start.astimezone(local_tz) == datetime(2021, 11, 1, tzinfo=local_tz) assert not pvpc_data.process_state_and_attributes(start) # After known prices are exausted, the state is flagged as unavailable From 40fe9e37abe07bd172139a034dfb1f24f5ead0ef Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 20:43:00 +0100 Subject: [PATCH 04/13] :sparkles: Add alternative data-source from 'apidatos.ree.es' * Implement data parsing from `apidatos.ree.es`, using endpoint at `/es/datos/mercados/precios-mercados-tiempo-real` * Add `data_source` parameter with valid keys 'apidatos' and 'esios_public', setting the new one as default ;-) * Remove retry call if 403 status is received, but maintain the User-Agent loop, and also toggle the data-source for the next call * Move old ATTRIBUTION to `.attribution` property, as function of the data-source --- aiopvpc/const.py | 13 ++++++- aiopvpc/parser.py | 86 +++++++++++++++++++++++++++++++++++++++++--- aiopvpc/pvpc_data.py | 56 ++++++++++++++--------------- 3 files changed, 120 insertions(+), 35 deletions(-) diff --git a/aiopvpc/const.py b/aiopvpc/const.py index 409833a..02616eb 100644 --- a/aiopvpc/const.py +++ b/aiopvpc/const.py @@ -3,6 +3,7 @@ """ import sys from datetime import date +from typing import Dict, Literal if sys.version_info[:2] >= (3, 9): # pragma: no cover import zoneinfo # pylint: disable=import-error @@ -28,8 +29,18 @@ DEFAULT_TIMEOUT = 5 PRICE_PRECISION = 5 + +DataSource = Literal["esios_public", "apidatos"] # , "esios" URL_PVPC_RESOURCE = ( "https://api.esios.ree.es/archives/70/download_json" "?locale=es&date={day:%Y-%m-%d}" ) -ATTRIBUTION = "Data retrieved from api.esios.ree.es by REE" +URL_APIDATOS_PRICES_RESOURCE = ( + "https://apidatos.ree.es/es/datos/mercados/precios-mercados-tiempo-real" + "?time_trunc=hour" + "&start_date={start:%Y-%m-%dT%H:%M}&end_date={end:%Y-%m-%dT%H:%M}" +) +ATTRIBUTIONS: Dict[DataSource, str] = { + "esios_public": "Data retrieved from api.esios.ree.es by REE", + "apidatos": "Data retrieved from apidatos.ree.es by REE", +} diff --git a/aiopvpc/parser.py b/aiopvpc/parser.py index c504e37..42e160b 100644 --- a/aiopvpc/parser.py +++ b/aiopvpc/parser.py @@ -5,14 +5,59 @@ * Parser for the contents of the JSON files """ from datetime import datetime, timedelta -from typing import Any, Dict, Union +from typing import Any, Dict, TypedDict -from aiopvpc.const import PRICE_PRECISION, REFERENCE_TZ, UTC_TZ, zoneinfo +from aiopvpc.const import ( + DataSource, + PRICE_PRECISION, + REFERENCE_TZ, + URL_APIDATOS_PRICES_RESOURCE, + URL_PVPC_RESOURCE, + UTC_TZ, + zoneinfo, +) -def extract_pvpc_data( +class PricesResponse(TypedDict): + """Data schema for parsed prices coming from `apidatos.ree.es`.""" + + name: str + data_id: str + last_update: datetime + unit: str + series: Dict[str, Dict[datetime, float]] + + +def extract_prices_from_apidatos_ree( + data: Dict[str, Any], tz: zoneinfo.ZoneInfo = REFERENCE_TZ +) -> PricesResponse: + """Parse the contents of a query to 'precios-mercados-tiempo-real'.""" + ref_ts = datetime(2021, 1, 1, tzinfo=REFERENCE_TZ).astimezone(UTC_TZ) + loc_ts = datetime(2021, 1, 1, tzinfo=tz).astimezone(UTC_TZ) + loc_ts - ref_ts.astimezone(UTC_TZ) + offset_timezone = loc_ts - ref_ts + + def _parse_dt(ts: str) -> datetime: + return datetime.fromisoformat(ts).astimezone(UTC_TZ) + offset_timezone + + return PricesResponse( + name=data["data"]["type"], + data_id=data["data"]["id"], + last_update=_parse_dt(data["data"]["attributes"]["last-update"]), + unit="€/kWh", + series={ + data_series["type"].replace(" (€/MWh)", ""): { + _parse_dt(price["datetime"]): round(price["value"] / 1000.0, 5) + for price in data_series["attributes"]["values"] + } + for data_series in data["included"] + }, + ) + + +def extract_prices_from_esios_public( data: Dict[str, Any], key: str, tz: zoneinfo.ZoneInfo = REFERENCE_TZ -) -> Union[Dict[datetime, float], Dict[datetime, Dict[str, float]]]: +) -> PricesResponse: """Parse the contents of a daily PVPC json file.""" ts_init = datetime( *datetime.strptime(data["PVPC"][0]["Dia"], "%d/%m/%Y").timetuple()[:3], @@ -22,7 +67,38 @@ def extract_pvpc_data( def _parse_tariff_val(value, prec=PRICE_PRECISION) -> float: return round(float(value.replace(",", ".")) / 1000.0, prec) - return { + pvpc_prices = { ts_init + timedelta(hours=i): _parse_tariff_val(values_hour[key]) for i, values_hour in enumerate(data["PVPC"]) } + + return PricesResponse( + name="PVPC ESIOS", + data_id="legacy", + last_update=datetime.utcnow().replace(microsecond=0, tzinfo=UTC_TZ), + unit="€/kWh", + series={"PVPC": pvpc_prices}, + ) + + +def extract_pvpc_data( + data: Dict[str, Any], url: str, key: str, tz: zoneinfo.ZoneInfo = REFERENCE_TZ +) -> Dict[datetime, float]: + """Parse the contents of a daily PVPC json file.""" + if url.startswith("https://api.esios.ree.es/archives"): + prices_data = extract_prices_from_esios_public(data, key, tz) + elif url.startswith("https://apidatos.ree.es"): + prices_data = extract_prices_from_apidatos_ree(data, tz) + else: + raise NotImplementedError(f"Data source not known: {url} >{data}") + return prices_data["series"]["PVPC"] + + +def get_url_prices(source: DataSource, now_local_ref: datetime) -> str: + if source == "esios_public": + return URL_PVPC_RESOURCE.format(day=now_local_ref.date()) + + start = now_local_ref.replace(hour=0, minute=0) + end = now_local_ref.replace(hour=23, minute=59) + # TODO implement geo_zones!!! + return URL_APIDATOS_PRICES_RESOURCE.format(start=start, end=end) diff --git a/aiopvpc/pvpc_data.py b/aiopvpc/pvpc_data.py index 679ef2f..beab0b9 100644 --- a/aiopvpc/pvpc_data.py +++ b/aiopvpc/pvpc_data.py @@ -8,7 +8,7 @@ import asyncio import logging from collections import deque -from datetime import date, datetime, timedelta +from datetime import datetime, timedelta from random import random from typing import Any, Dict, Optional, Union @@ -16,18 +16,18 @@ import async_timeout from aiopvpc.const import ( - ATTRIBUTION, + ATTRIBUTIONS, + DataSource, DATE_CHANGE_TO_20TD, DEFAULT_POWER_KW, DEFAULT_TIMEOUT, REFERENCE_TZ, TARIFF2ID, TARIFFS, - URL_PVPC_RESOURCE, UTC_TZ, zoneinfo, ) -from aiopvpc.parser import extract_pvpc_data +from aiopvpc.parser import extract_pvpc_data, get_url_prices from aiopvpc.prices import make_price_sensor_attributes from aiopvpc.pvpc_tariff import get_current_and_next_tariff_periods from aiopvpc.utils import ensure_utc_time @@ -81,6 +81,7 @@ def __init__( power: float = DEFAULT_POWER_KW, power_valley: float = DEFAULT_POWER_KW, timeout: float = DEFAULT_TIMEOUT, + data_source: DataSource = "apidatos", # "esios_public", ): self.source_available = True self.state: Optional[float] = None @@ -89,6 +90,7 @@ def __init__( self.timeout = timeout self._session = websession + self._data_source = data_source self._user_agents = deque(sorted(_STANDARD_USER_AGENTS, key=lambda x: random())) self._headers = { "User-Agent": self._user_agents[0], @@ -110,29 +112,18 @@ async def _api_get_prices(self, url: str, tariff: str) -> Dict[datetime, Any]: resp = await self._session.get(url, headers=self._headers) if resp.status < 400: data = await resp.json() - return extract_pvpc_data(data, tariff, tz=self._local_timezone) + return extract_pvpc_data(data, url, tariff, tz=self._local_timezone) elif resp.status == 403: # pragma: no cover - _LOGGER.warning( - "Forbidden error with '%s' -> Headers: %s", url, resp.headers - ) - # loop user-agent + _LOGGER.warning("Forbidden error with '%s': %s", self._data_source, url) + # loop user-agent and data-source self._user_agents.rotate() self._headers["User-Agent"] = self._user_agents[0] - # and retry - resp = await self._session.get(url, headers=self._headers) - if resp.status < 400: - data = await resp.json() - return extract_pvpc_data(data, tariff, tz=self._local_timezone) - elif resp.status == 403: - _LOGGER.error( - "Repeaed forbidden error with '%s' -> Headers: %s", - url, - resp.headers, - ) - self._headers.pop("User-Agent") + self._data_source = ( + "apidatos" if self._data_source == "esios_public" else "esios_public" + ) return {} - async def _download_pvpc_prices(self, day: date) -> Dict[datetime, Any]: + async def _download_pvpc_prices(self, now: datetime) -> Dict[datetime, Any]: """ PVPC data extractor. @@ -144,15 +135,14 @@ async def _download_pvpc_prices(self, day: date) -> Dict[datetime, Any]: Prices are referenced with datetimes in UTC. """ - assert day >= DATE_CHANGE_TO_20TD, "Deprecated support for old tariffs" - url = URL_PVPC_RESOURCE.format(day=day) + assert now.date() >= DATE_CHANGE_TO_20TD, "No support for old tariffs" + url = get_url_prices(self._data_source, now) tariff = TARIFF2ID[self.tariff] - try: async with async_timeout.timeout(2 * self.timeout): return await self._api_get_prices(url, tariff) except KeyError: - _LOGGER.debug("Bad try on getting prices for %s", day) + _LOGGER.debug("Bad try on getting prices for %s", now) except asyncio.TimeoutError: if self.source_available: _LOGGER.warning("Timeout error requesting data from '%s'", url) @@ -223,13 +213,13 @@ async def async_update_prices(self, now: datetime) -> Dict[datetime, float]: txt_last, local_ref_now.date(), ) - prices = await self._download_pvpc_prices(local_ref_now.date()) + prices = await self._download_pvpc_prices(local_ref_now) if not prices: return prices # At evening, it is possible to retrieve next day prices if local_ref_now.hour >= 20: - next_day = (local_ref_now + timedelta(days=1)).date() + next_day = local_ref_now + timedelta(days=1) prices_fut = await self._download_pvpc_prices(next_day) if prices_fut: prices.update(prices_fut) @@ -243,6 +233,11 @@ async def async_update_prices(self, now: datetime) -> Dict[datetime, float]: return prices + @property + def attribution(self) -> str: + """Return data-source attribution string.""" + return ATTRIBUTIONS[self._data_source] + def process_state_and_attributes(self, utc_now: datetime) -> bool: """ Generate the current state and sensor attributes. @@ -254,7 +249,10 @@ def process_state_and_attributes(self, utc_now: datetime) -> bool: If not, it is converted to UTC from the original timezone, or set as UTC-time if it is a naive datetime. """ - attributes: Dict[str, Any] = {"attribution": ATTRIBUTION, "tariff": self.tariff} + attributes: Dict[str, Any] = { + "attribution": self.attribution, + "tariff": self.tariff, + } utc_time = ensure_utc_time(utc_now.replace(minute=0, second=0, microsecond=0)) actual_time = utc_time.astimezone(self._local_timezone) # todo power_period/power_price €/kW*año From dd6bb6daa2625ba4a380b8b01bc010bd155e35d1 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 20:44:26 +0100 Subject: [PATCH 05/13] :truck: Add test patterns from new data-source --- .../PRICES_APIDATOS_2021_06_01.json | 290 +++++++++++++++++ .../PRICES_APIDATOS_2021_10_30.json | 290 +++++++++++++++++ .../PRICES_APIDATOS_2021_10_31.json | 300 ++++++++++++++++++ tests/conftest.py | 21 +- 4 files changed, 897 insertions(+), 4 deletions(-) create mode 100644 tests/api_examples/PRICES_APIDATOS_2021_06_01.json create mode 100644 tests/api_examples/PRICES_APIDATOS_2021_10_30.json create mode 100644 tests/api_examples/PRICES_APIDATOS_2021_10_31.json diff --git a/tests/api_examples/PRICES_APIDATOS_2021_06_01.json b/tests/api_examples/PRICES_APIDATOS_2021_06_01.json new file mode 100644 index 0000000..efe173b --- /dev/null +++ b/tests/api_examples/PRICES_APIDATOS_2021_06_01.json @@ -0,0 +1,290 @@ +{ + "data": { + "type": "Precios mercado peninsular en tiempo real", + "id": "mer13", + "attributes": { + "title": "Precios mercado peninsular en tiempo real", + "last-update": "2021-05-31T20:19:18.000+02:00", + "description": null + }, + "meta": { + "cache-control": { + "cache": "MISS" + } + } + }, + "included": [ + { + "type": "PVPC (\u20ac\/MWh)", + "id": "1001", + "groupId": null, + "attributes": { + "title": "PVPC (\u20ac\/MWh)", + "description": null, + "color": "#ffcf09", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-05-31T20:19:18.000+02:00", + "values": [ + { + "value": 116.33, + "percentage": 0.5651751445367537, + "datetime": "2021-06-01T00:00:00.000+02:00" + }, + { + "value": 115.95, + "percentage": 0.5682152308144663, + "datetime": "2021-06-01T01:00:00.000+02:00" + }, + { + "value": 114.89, + "percentage": 0.5699191428146237, + "datetime": "2021-06-01T02:00:00.000+02:00" + }, + { + "value": 114.96, + "percentage": 0.5699271230975163, + "datetime": "2021-06-01T03:00:00.000+02:00" + }, + { + "value": 114.84, + "percentage": 0.5698124441798154, + "datetime": "2021-06-01T04:00:00.000+02:00" + }, + { + "value": 116.03, + "percentage": 0.5686908787923345, + "datetime": "2021-06-01T05:00:00.000+02:00" + }, + { + "value": 116.29, + "percentage": 0.5650906263666845, + "datetime": "2021-06-01T06:00:00.000+02:00" + }, + { + "value": 115.7, + "percentage": 0.559477756286267, + "datetime": "2021-06-01T07:00:00.000+02:00" + }, + { + "value": 152.89, + "percentage": 0.6234555315418179, + "datetime": "2021-06-01T08:00:00.000+02:00" + }, + { + "value": 150.83, + "percentage": 0.6213900218349606, + "datetime": "2021-06-01T09:00:00.000+02:00" + }, + { + "value": 242.62, + "percentage": 0.7283261287223823, + "datetime": "2021-06-01T10:00:00.000+02:00" + }, + { + "value": 240.5, + "percentage": 0.7316924761933737, + "datetime": "2021-06-01T11:00:00.000+02:00" + }, + { + "value": 238.09, + "percentage": 0.734868360134572, + "datetime": "2021-06-01T12:00:00.000+02:00" + }, + { + "value": 235.3, + "percentage": 0.7386363636363636, + "datetime": "2021-06-01T13:00:00.000+02:00" + }, + { + "value": 137.96, + "percentage": 0.6353504651376992, + "datetime": "2021-06-01T14:00:00.000+02:00" + }, + { + "value": 132.88, + "percentage": 0.6406943105110897, + "datetime": "2021-06-01T15:00:00.000+02:00" + }, + { + "value": 131.93, + "percentage": 0.6403436392758336, + "datetime": "2021-06-01T16:00:00.000+02:00" + }, + { + "value": 135.99, + "percentage": 0.6354672897196262, + "datetime": "2021-06-01T17:00:00.000+02:00" + }, + { + "value": 231.44, + "percentage": 0.7437256981265464, + "datetime": "2021-06-01T18:00:00.000+02:00" + }, + { + "value": 240.4, + "percentage": 0.7349434423723632, + "datetime": "2021-06-01T19:00:00.000+02:00" + }, + { + "value": 246.2, + "percentage": 0.7314319667260842, + "datetime": "2021-06-01T20:00:00.000+02:00" + }, + { + "value": 248.08, + "percentage": 0.7283189478010687, + "datetime": "2021-06-01T21:00:00.000+02:00" + }, + { + "value": 155.91, + "percentage": 0.627935075919288, + "datetime": "2021-06-01T22:00:00.000+02:00" + }, + { + "value": 156.5, + "percentage": 0.6309975002015967, + "datetime": "2021-06-01T23:00:00.000+02:00" + } + ] + } + }, + { + "type": "Spot market price (\u20ac\/MWh)", + "id": "600", + "groupId": null, + "attributes": { + "title": "Spot market price (\u20ac\/MWh)", + "description": null, + "color": "#df4a32", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-05-31T13:39:43.000+02:00", + "values": [ + { + "value": 89.5, + "percentage": 0.4348248554632464, + "datetime": "2021-06-01T00:00:00.000+02:00" + }, + { + "value": 88.11, + "percentage": 0.43178476918553366, + "datetime": "2021-06-01T01:00:00.000+02:00" + }, + { + "value": 86.7, + "percentage": 0.43008085718537625, + "datetime": "2021-06-01T02:00:00.000+02:00" + }, + { + "value": 86.75, + "percentage": 0.4300728769024838, + "datetime": "2021-06-01T03:00:00.000+02:00" + }, + { + "value": 86.7, + "percentage": 0.43018755582018453, + "datetime": "2021-06-01T04:00:00.000+02:00" + }, + { + "value": 88, + "percentage": 0.4313091212076655, + "datetime": "2021-06-01T05:00:00.000+02:00" + }, + { + "value": 89.5, + "percentage": 0.4349093736333155, + "datetime": "2021-06-01T06:00:00.000+02:00" + }, + { + "value": 91.1, + "percentage": 0.440522243713733, + "datetime": "2021-06-01T07:00:00.000+02:00" + }, + { + "value": 92.34, + "percentage": 0.3765444684581821, + "datetime": "2021-06-01T08:00:00.000+02:00" + }, + { + "value": 91.9, + "percentage": 0.37860997816503933, + "datetime": "2021-06-01T09:00:00.000+02:00" + }, + { + "value": 90.5, + "percentage": 0.27167387127761766, + "datetime": "2021-06-01T10:00:00.000+02:00" + }, + { + "value": 88.19, + "percentage": 0.2683075238066263, + "datetime": "2021-06-01T11:00:00.000+02:00" + }, + { + "value": 85.9, + "percentage": 0.265131639865428, + "datetime": "2021-06-01T12:00:00.000+02:00" + }, + { + "value": 83.26, + "percentage": 0.26136363636363635, + "datetime": "2021-06-01T13:00:00.000+02:00" + }, + { + "value": 79.18, + "percentage": 0.36464953486230084, + "datetime": "2021-06-01T14:00:00.000+02:00" + }, + { + "value": 74.52, + "percentage": 0.35930568948891034, + "datetime": "2021-06-01T15:00:00.000+02:00" + }, + { + "value": 74.1, + "percentage": 0.35965636072416635, + "datetime": "2021-06-01T16:00:00.000+02:00" + }, + { + "value": 78.01, + "percentage": 0.3645327102803739, + "datetime": "2021-06-01T17:00:00.000+02:00" + }, + { + "value": 79.75, + "percentage": 0.2562743018734535, + "datetime": "2021-06-01T18:00:00.000+02:00" + }, + { + "value": 86.7, + "percentage": 0.2650565576276368, + "datetime": "2021-06-01T19:00:00.000+02:00" + }, + { + "value": 90.4, + "percentage": 0.26856803327391565, + "datetime": "2021-06-01T20:00:00.000+02:00" + }, + { + "value": 92.54, + "percentage": 0.27168105219893135, + "datetime": "2021-06-01T21:00:00.000+02:00" + }, + { + "value": 92.38, + "percentage": 0.37206492408071207, + "datetime": "2021-06-01T22:00:00.000+02:00" + }, + { + "value": 91.52, + "percentage": 0.3690024997984034, + "datetime": "2021-06-01T23:00:00.000+02:00" + } + ] + } + } + ] +} diff --git a/tests/api_examples/PRICES_APIDATOS_2021_10_30.json b/tests/api_examples/PRICES_APIDATOS_2021_10_30.json new file mode 100644 index 0000000..beb20a1 --- /dev/null +++ b/tests/api_examples/PRICES_APIDATOS_2021_10_30.json @@ -0,0 +1,290 @@ +{ + "data": { + "type": "Precios mercado peninsular en tiempo real", + "id": "mer13", + "attributes": { + "title": "Precios mercado peninsular en tiempo real", + "last-update": "2021-10-29T20:17:00.000+02:00", + "description": null + }, + "meta": { + "cache-control": { + "cache": "MISS" + } + } + }, + "included": [ + { + "type": "PVPC (\u20ac\/MWh)", + "id": "1001", + "groupId": null, + "attributes": { + "title": "PVPC (\u20ac\/MWh)", + "description": null, + "color": "#ffcf09", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-10-29T20:17:00.000+02:00", + "values": [ + { + "value": 131.04, + "percentage": 0.567174515235457, + "datetime": "2021-10-30T00:00:00.000+02:00" + }, + { + "value": 120.55, + "percentage": 0.5722491218076521, + "datetime": "2021-10-30T01:00:00.000+02:00" + }, + { + "value": 103.97, + "percentage": 0.5794137316094516, + "datetime": "2021-10-30T02:00:00.000+02:00" + }, + { + "value": 92.51, + "percentage": 0.5911937627811861, + "datetime": "2021-10-30T03:00:00.000+02:00" + }, + { + "value": 87.43, + "percentage": 0.5979346190671592, + "datetime": 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"2021-10-30T04:00:00.000+02:00" + }, + { + "value": 61.05, + "percentage": 0.4018033434250362, + "datetime": "2021-10-30T05:00:00.000+02:00" + }, + { + "value": 77.36, + "percentage": 0.41649617745235273, + "datetime": "2021-10-30T06:00:00.000+02:00" + }, + { + "value": 92.06, + "percentage": 0.42279783227702766, + "datetime": "2021-10-30T07:00:00.000+02:00" + }, + { + "value": 117.65, + "percentage": 0.43443742845537464, + "datetime": "2021-10-30T08:00:00.000+02:00" + }, + { + "value": 149.89, + "percentage": 0.447780366851885, + "datetime": "2021-10-30T09:00:00.000+02:00" + }, + { + "value": 155.21, + "percentage": 0.4514805980568969, + "datetime": "2021-10-30T10:00:00.000+02:00" + }, + { + "value": 148.29, + "percentage": 0.4515804860222912, + "datetime": "2021-10-30T11:00:00.000+02:00" + }, + { + "value": 144.99, + "percentage": 0.45130264263703435, + "datetime": "2021-10-30T12:00:00.000+02:00" + }, + { + "value": 129.89, + "percentage": 0.44658758810383353, + "datetime": "2021-10-30T13:00:00.000+02:00" + }, + { + "value": 120, + "percentage": 0.44553352639786137, + "datetime": "2021-10-30T14:00:00.000+02:00" + }, + { + "value": 105.76, + "percentage": 0.4396225630793532, + "datetime": "2021-10-30T15:00:00.000+02:00" + }, + { + "value": 133.46, + "percentage": 0.44824343386847587, + "datetime": "2021-10-30T16:00:00.000+02:00" + }, + { + "value": 155.86, + "percentage": 0.4510621056896452, + "datetime": "2021-10-30T17:00:00.000+02:00" + }, + { + "value": 167.92, + "percentage": 0.4486001282325283, + "datetime": "2021-10-30T18:00:00.000+02:00" + }, + { + "value": 186.21, + "percentage": 0.450097894660511, + "datetime": "2021-10-30T19:00:00.000+02:00" + }, + { + "value": 192.07, + "percentage": 0.45152569467299825, + "datetime": "2021-10-30T20:00:00.000+02:00" + }, + { + "value": 178.51, + "percentage": 0.4494096321844868, + "datetime": "2021-10-30T21:00:00.000+02:00" + }, + { + "value": 151.45, + "percentage": 0.444721773601527, + "datetime": "2021-10-30T22:00:00.000+02:00" + }, + { + "value": 132.66, + "percentage": 0.4402044066896734, + "datetime": "2021-10-30T23:00:00.000+02:00" + } + ] + } + } + ] +} diff --git a/tests/api_examples/PRICES_APIDATOS_2021_10_31.json b/tests/api_examples/PRICES_APIDATOS_2021_10_31.json new file mode 100644 index 0000000..3e8300a --- /dev/null +++ b/tests/api_examples/PRICES_APIDATOS_2021_10_31.json @@ -0,0 +1,300 @@ +{ + "data": { + "type": "Precios mercado peninsular en tiempo real", + "id": "mer13", + "attributes": { + "title": "Precios mercado peninsular en tiempo real", + "last-update": "2021-10-30T20:16:46.000+02:00", + "description": null + }, + "meta": { + "cache-control": { + "cache": "MISS" + } + } + }, + "included": [ + { + "type": "PVPC (\u20ac\/MWh)", + "id": "1001", + "groupId": null, + "attributes": { + "title": "PVPC (\u20ac\/MWh)", + "description": null, + "color": "#ffcf09", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-10-30T20:16:46.000+02:00", + "values": [ + { + "value": 171.48, + "percentage": 0.5604654203163812, + "datetime": "2021-10-31T00:00:00.000+02:00" + }, + { + "value": 123.9, + "percentage": 0.5842135043379857, + "datetime": "2021-10-31T01:00:00.000+02:00" + }, + { + "value": 109.55, + "percentage": 0.5943145445668095, + "datetime": "2021-10-31T02:00:00.000+02:00" + }, + { + "value": 104.85, + "percentage": 0.6018252783836529, + "datetime": "2021-10-31T02:00:00.000+01:00" + }, + { + "value": 92.03, + "percentage": 0.6170712082606947, + "datetime": "2021-10-31T03:00:00.000+01:00" + }, + { + "value": 92.99, + "percentage": 0.6166445623342174, + "datetime": "2021-10-31T04:00:00.000+01:00" + }, + { + "value": 86.87, + "percentage": 0.6213432515556827, + "datetime": "2021-10-31T05:00:00.000+01:00" + }, + { + "value": 86.2, + "percentage": 0.6163746871648195, + "datetime": "2021-10-31T06:00:00.000+01:00" + }, + { + "value": 88.03, + "percentage": 0.6111921127542873, + "datetime": "2021-10-31T07:00:00.000+01:00" + }, + { + "value": 81.82, + "percentage": 0.6078300274868138, + "datetime": "2021-10-31T08:00:00.000+01:00" + }, + { + "value": 102.63, + "percentage": 0.5886772972352874, + "datetime": "2021-10-31T09:00:00.000+01:00" + }, + { + "value": 91.09, + "percentage": 0.5836109687339827, + "datetime": "2021-10-31T10:00:00.000+01:00" + }, + { + "value": 91.1, + "percentage": 0.5839369271200564, + "datetime": "2021-10-31T11:00:00.000+01:00" + }, + { + "value": 86.49, + "percentage": 0.5838002024974689, + "datetime": "2021-10-31T12:00:00.000+01:00" + }, + { + "value": 79.78, + "percentage": 0.5870493009565857, + "datetime": "2021-10-31T13:00:00.000+01:00" + }, + { + "value": 80.8, + "percentage": 0.5899963490324936, + "datetime": "2021-10-31T14:00:00.000+01:00" + }, + { + "value": 81.34, + "percentage": 0.5965967434355288, + "datetime": "2021-10-31T15:00:00.000+01:00" + }, + { + "value": 92.09, + "percentage": 0.5888107416879795, + "datetime": "2021-10-31T16:00:00.000+01:00" + }, + { + "value": 111.3, + "percentage": 0.5766839378238342, + "datetime": "2021-10-31T17:00:00.000+01:00" + }, + { + "value": 122.85, + "percentage": 0.571927374301676, + "datetime": "2021-10-31T18:00:00.000+01:00" + }, + { + "value": 131.87, + "percentage": 0.5686257599931007, + "datetime": "2021-10-31T19:00:00.000+01:00" + }, + { + "value": 185.38, + "percentage": 0.5560621512988182, + "datetime": "2021-10-31T20:00:00.000+01:00" + }, + { + "value": 165.54, + "percentage": 0.5591811917308472, + "datetime": "2021-10-31T21:00:00.000+01:00" + }, + { + "value": 152.39, + "percentage": 0.5639270251267438, + "datetime": "2021-10-31T22:00:00.000+01:00" + }, + { + "value": 146.12, + "percentage": 0.564126322291715, + "datetime": "2021-10-31T23:00:00.000+01:00" + } + ] + } + }, + { + "type": "Precio mercado spot (\u20ac\/MWh)", + "id": "600", + "groupId": null, + "attributes": { + "title": "Precio mercado spot (\u20ac\/MWh)", + "description": null, + "color": "#df4a32", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-10-30T13:39:58.000+02:00", + "values": [ + { + "value": 134.48, + "percentage": 0.43953457968361875, + "datetime": "2021-10-31T00:00:00.000+02:00" + }, + { + "value": 88.18, + "percentage": 0.41578649566201437, + "datetime": "2021-10-31T01:00:00.000+02:00" + }, + { + "value": 74.78, + "percentage": 0.4056854554331905, + "datetime": "2021-10-31T02:00:00.000+02:00" + }, + { + "value": 69.37, + "percentage": 0.39817472161634715, + "datetime": "2021-10-31T02:00:00.000+01:00" + }, + { + "value": 57.11, + "percentage": 0.3829287917393054, + "datetime": "2021-10-31T03:00:00.000+01:00" + }, + { + "value": 57.81, + "percentage": 0.3833554376657825, + "datetime": "2021-10-31T04:00:00.000+01:00" + }, + { + "value": 52.94, + "percentage": 0.3786567484443173, + "datetime": "2021-10-31T05:00:00.000+01:00" + }, + { + "value": 53.65, + "percentage": 0.38362531283518053, + "datetime": "2021-10-31T06:00:00.000+01:00" + }, + { + "value": 56, + "percentage": 0.3888078872457127, + "datetime": "2021-10-31T07:00:00.000+01:00" + }, + { + "value": 52.79, + "percentage": 0.3921699725131863, + "datetime": "2021-10-31T08:00:00.000+01:00" + }, + { + "value": 71.71, + "percentage": 0.41132270276471267, + "datetime": "2021-10-31T09:00:00.000+01:00" + }, + { + "value": 64.99, + "percentage": 0.41638903126601745, + "datetime": "2021-10-31T10:00:00.000+01:00" + }, + { + "value": 64.91, + "percentage": 0.4160630728799436, + "datetime": "2021-10-31T11:00:00.000+01:00" + }, + { + "value": 61.66, + "percentage": 0.4161997975025313, + "datetime": "2021-10-31T12:00:00.000+01:00" + }, + { + "value": 56.12, + "percentage": 0.41295069904341425, + "datetime": "2021-10-31T13:00:00.000+01:00" + }, + { + "value": 56.15, + "percentage": 0.4100036509675064, + "datetime": "2021-10-31T14:00:00.000+01:00" + }, + { + "value": 55, + "percentage": 0.4034032565644712, + "datetime": "2021-10-31T15:00:00.000+01:00" + }, + { + "value": 64.31, + "percentage": 0.41118925831202047, + "datetime": "2021-10-31T16:00:00.000+01:00" + }, + { + "value": 81.7, + "percentage": 0.4233160621761658, + "datetime": "2021-10-31T17:00:00.000+01:00" + }, + { + "value": 91.95, + "percentage": 0.428072625698324, + "datetime": "2021-10-31T18:00:00.000+01:00" + }, + { + "value": 100.04, + "percentage": 0.4313742400068992, + "datetime": "2021-10-31T19:00:00.000+01:00" + }, + { + "value": 148, + "percentage": 0.44393784870118186, + "datetime": "2021-10-31T20:00:00.000+01:00" + }, + { + "value": 130.5, + "percentage": 0.4408188082691529, + "datetime": "2021-10-31T21:00:00.000+01:00" + }, + { + "value": 117.84, + "percentage": 0.4360729748732561, + "datetime": "2021-10-31T22:00:00.000+01:00" + }, + { + "value": 112.9, + "percentage": 0.4358736777082851, + "datetime": "2021-10-31T23:00:00.000+01:00" + } + ] + } + } + ] +} diff --git a/tests/conftest.py b/tests/conftest.py index 49fddd8..c4d3b12 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -16,6 +16,9 @@ FIXTURE_JSON_DATA_2021_10_31 = "PVPC_CURV_DD_2021_10_31.json" FIXTURE_JSON_DATA_2022_03_27 = "PVPC_CURV_DD_2022_03_27.json" FIXTURE_JSON_DATA_2021_06_01 = "PVPC_CURV_DD_2021_06_01.json" +FIXTURE_JSON_DATA_S2_2021_06_01 = "PRICES_APIDATOS_2021_06_01.json" +FIXTURE_JSON_DATA_S2_2021_10_30 = "PRICES_APIDATOS_2021_10_30.json" +FIXTURE_JSON_DATA_S2_2021_10_31 = "PRICES_APIDATOS_2021_10_31.json" _DEFAULT_EMPTY_VALUE = {"message": "No values for specified archive"} @@ -46,7 +49,12 @@ def __init__(self, status=200, exc=None): self.status = status self.exc = exc - self.responses = { + self.responses_apidatos = { + date(2021, 10, 30): load_fixture(FIXTURE_JSON_DATA_S2_2021_10_30), + date(2021, 10, 31): load_fixture(FIXTURE_JSON_DATA_S2_2021_10_31), + date(2021, 6, 1): load_fixture(FIXTURE_JSON_DATA_S2_2021_06_01), + } + self.responses_esios = { date(2022, 3, 27): load_fixture(FIXTURE_JSON_DATA_2022_03_27), date(2021, 10, 30): load_fixture(FIXTURE_JSON_DATA_2021_10_30), date(2021, 10, 31): load_fixture(FIXTURE_JSON_DATA_2021_10_31), @@ -60,11 +68,16 @@ async def json(self, *_args, **_kwargs): async def get(self, url, *_args, **_kwargs): """Dumb await.""" self._counter += 1 - day = datetime.fromisoformat(url.split("=")[-1]).date() if self.exc: raise self.exc - if day in self.responses: - self._raw_response = self.responses[day] + key = datetime.fromisoformat(url.split("=")[-1]).date() + if ( + url.startswith("https://api.esios.ree.es/archives") + and key in self.responses_esios + ): + self._raw_response = self.responses_esios[key] + elif url.startswith("https://apidatos.ree.es"): + self._raw_response = self.responses_apidatos[key] else: self._raw_response = _DEFAULT_EMPTY_VALUE return self From 946a6a465f57f40294c65c47c5fdbe5724963f79 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sat, 4 Dec 2021 20:45:37 +0100 Subject: [PATCH 06/13] :white_check_mark: Adjust tests for new data-source --- tests/test_pvpc.py | 63 +--------------------------- tests/test_pvpc_parsing.py | 79 ++++++++++++++++++++++++++++++++++++ tests/test_real_api_calls.py | 27 ++++++++---- 3 files changed, 101 insertions(+), 68 deletions(-) create mode 100644 tests/test_pvpc_parsing.py diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index 55e61e9..cee3858 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -11,61 +11,6 @@ from tests.conftest import MockAsyncSession, TZ_TEST -@pytest.mark.parametrize( - "day_str, timezone, zone_cm, num_prices, num_calls, num_prices_8h, available_8h", - ( - ("2021-10-30 00:00:00+08:00", TZ_TEST, False, 0, 1, 0, False), - ("2021-10-30 00:00:00", TZ_TEST, False, 24, 1, 24, True), - ("2021-10-31 00:00:00", TZ_TEST, False, 25, 1, 25, True), - ("2022-03-27 20:00:00", TZ_TEST, False, 23, 2, 23, False), - ("2022-03-27 20:00:00+04:00", TZ_TEST, False, 23, 1, 23, False), - ("2021-10-30 21:00:00", TZ_TEST, False, 49, 2, 26, True), - ("2021-10-30 21:00:00+01:00", TZ_TEST, False, 49, 2, 26, True), - ("2021-10-30 00:00:00", REFERENCE_TZ, True, 24, 1, 24, True), - ("2021-10-31 00:00:00", REFERENCE_TZ, True, 25, 1, 25, True), - ("2022-03-27 20:00:00", REFERENCE_TZ, True, 23, 2, 23, False), - ("2021-10-30 21:00:00", REFERENCE_TZ, True, 49, 2, 25, True), - ("2021-06-01 09:00:00", REFERENCE_TZ, True, 24, 1, 24, True), - ), -) -@pytest.mark.asyncio -async def test_price_extract( - day_str, - timezone, - zone_cm, - num_prices, - num_calls, - num_prices_8h, - available_8h, -): - """Test data parsing of official API files.""" - day = datetime.fromisoformat(day_str) - mock_session = MockAsyncSession() - - pvpc_data = PVPCData( - tariff="2.0TD", - local_timezone=timezone, - websession=mock_session, - zone_ceuta_melilla=zone_cm, - ) - - pvpc_data.source_available = True - assert not pvpc_data.process_state_and_attributes(day) - assert mock_session.call_count == 0 - - await pvpc_data.async_update_prices(day) - pvpc_data.process_state_and_attributes(day) - assert len(pvpc_data._current_prices) == num_prices - assert mock_session.call_count == num_calls - - has_prices = pvpc_data.process_state_and_attributes(day + timedelta(hours=10)) - assert len(pvpc_data._current_prices) == num_prices_8h - assert has_prices == available_8h - if has_prices: - last_dt, last_p = list(pvpc_data._current_prices.items())[-1] - assert last_dt.astimezone(timezone).hour == 23 - - @pytest.mark.parametrize( "available, day_str, num_log_msgs, status, exception", ( @@ -87,14 +32,10 @@ async def test_bad_downloads( caplog, ): """Test data parsing of official API files.""" - day = datetime.fromisoformat(day_str) + day = datetime.fromisoformat(day_str).astimezone(REFERENCE_TZ) mock_session = MockAsyncSession(status=status, exc=exception) with caplog.at_level(logging.INFO): - pvpc_data = PVPCData( - websession=mock_session, - tariff="2.0TD", - local_timezone=REFERENCE_TZ, - ) + pvpc_data = PVPCData(websession=mock_session, tariff="2.0TD") pvpc_data.source_available = available assert not pvpc_data.process_state_and_attributes(day) prices = await pvpc_data.async_update_prices(day) diff --git a/tests/test_pvpc_parsing.py b/tests/test_pvpc_parsing.py new file mode 100644 index 0000000..3eecb57 --- /dev/null +++ b/tests/test_pvpc_parsing.py @@ -0,0 +1,79 @@ +"""Tests for aiopvpc.""" +from datetime import datetime, timedelta + +import pytest + +from aiopvpc.const import REFERENCE_TZ, UTC_TZ +from aiopvpc.pvpc_data import PVPCData +from tests.conftest import MockAsyncSession, TZ_TEST + + +@pytest.mark.parametrize( + "ts, source, timezone, zone_cm, n_prices, n_calls, n_prices_8h, available_8h", + ( + ("2021-10-30 00:00:00+08:00", "apidatos", TZ_TEST, False, 0, 1, 0, False), + ("2021-10-30 00:00:00", "apidatos", TZ_TEST, False, 24, 1, 24, True), + ("2021-10-31 00:00:00", "apidatos", TZ_TEST, False, 25, 1, 25, True), + # ("2022-03-27 20:00:00", "apidatos", TZ_TEST, False, 23, 2, 23, False), + # ("2022-03-27 20:00:00+04:00", "apidatos", TZ_TEST, False, 23, 1, 23, False), + ("2021-10-30 21:00:00", "apidatos", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 21:00:00+01:00", "apidatos", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 00:00:00", "apidatos", REFERENCE_TZ, True, 24, 1, 24, True), + ("2021-10-31 00:00:00", "apidatos", REFERENCE_TZ, True, 25, 1, 25, True), + # ("2022-03-27 20:00:00", "apidatos", REFERENCE_TZ, True, 23, 2, 23, False), + ("2021-10-30 21:00:00", "apidatos", REFERENCE_TZ, True, 49, 2, 25, True), + ("2021-06-01 09:00:00", "apidatos", REFERENCE_TZ, True, 24, 1, 24, True), + ("2021-06-01 09:00:00", "apidatos", TZ_TEST, True, 24, 1, 24, True), + ("2021-10-30 00:00:00+08:00", "esios_public", TZ_TEST, False, 0, 1, 0, False), + ("2021-10-30 00:00:00", "esios_public", TZ_TEST, False, 24, 1, 24, True), + ("2021-10-31 00:00:00", "esios_public", TZ_TEST, False, 25, 1, 25, True), + ("2022-03-27 20:00:00", "esios_public", TZ_TEST, False, 23, 2, 23, False), + ("2022-03-27 20:00:00+04:00", "esios_public", TZ_TEST, False, 23, 1, 23, False), + ("2021-10-30 21:00:00", "esios_public", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 21:00:00+01:00", "esios_public", TZ_TEST, False, 49, 2, 26, True), + ("2021-10-30 00:00:00", "esios_public", REFERENCE_TZ, True, 24, 1, 24, True), + ("2021-10-31 00:00:00", "esios_public", REFERENCE_TZ, True, 25, 1, 25, True), + ("2022-03-27 20:00:00", "esios_public", REFERENCE_TZ, True, 23, 2, 23, False), + ("2021-10-30 21:00:00", "esios_public", REFERENCE_TZ, True, 49, 2, 25, True), + ("2021-06-01 09:00:00", "esios_public", REFERENCE_TZ, True, 24, 1, 24, True), + ("2021-06-01 09:00:00", "esios_public", TZ_TEST, True, 24, 1, 24, True), + ), +) +@pytest.mark.asyncio +async def test_price_extract( + ts, + source, + timezone, + zone_cm, + n_prices, + n_calls, + n_prices_8h, + available_8h, +): + """Test data parsing of official API files.""" + day = datetime.fromisoformat(ts).astimezone(UTC_TZ) + mock_session = MockAsyncSession() + + pvpc_data = PVPCData( + tariff="2.0TD", + local_timezone=timezone, + websession=mock_session, + zone_ceuta_melilla=zone_cm, + data_source=source, + ) + + pvpc_data.source_available = True + assert not pvpc_data.process_state_and_attributes(day) + assert mock_session.call_count == 0 + + await pvpc_data.async_update_prices(day) + pvpc_data.process_state_and_attributes(day) + assert len(pvpc_data._current_prices) == n_prices + assert mock_session.call_count == n_calls + + has_prices = pvpc_data.process_state_and_attributes(day + timedelta(hours=10)) + assert len(pvpc_data._current_prices) == n_prices_8h + assert has_prices == available_8h + if has_prices: + last_dt, last_p = list(pvpc_data._current_prices.items())[-1] + assert last_dt.astimezone(timezone).hour == 23 diff --git a/tests/test_real_api_calls.py b/tests/test_real_api_calls.py index 9d5a231..2011e8d 100644 --- a/tests/test_real_api_calls.py +++ b/tests/test_real_api_calls.py @@ -5,17 +5,30 @@ from aiohttp import ClientSession from aiopvpc import PVPCData +from aiopvpc.const import REFERENCE_TZ +from tests.conftest import TZ_TEST @pytest.mark.real_api_call @pytest.mark.asyncio -async def test_real_download_today_async(): +@pytest.mark.parametrize( + "data_source, tz", + ( + ("apidatos", REFERENCE_TZ), + ("esios_public", REFERENCE_TZ), + ("apidatos", TZ_TEST), + ("esios_public", TZ_TEST), + ), +) +async def test_real_download_today_async(data_source, tz): async with ClientSession() as session: - pvpc_handler = PVPCData("discrimination", websession=session) + pvpc_handler = PVPCData( + websession=session, + tariff="2.0TD", + data_source=data_source, + local_timezone=tz, + ) prices = await pvpc_handler.async_update_prices(datetime.utcnow()) assert 22 < len(prices) < 49 - - # Check error without session - pvpc_handler_bad = PVPCData("2.0TD") - with pytest.raises(AssertionError): - await pvpc_handler_bad.async_update_prices(datetime.utcnow()) + # from pprint import pprint + # pprint(prices) From 5632276b9d935a0ecc151f74f417e2d52b9203ee Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 12:35:19 +0100 Subject: [PATCH 07/13] :white_check_mark: Minor fixes on tests and more coverage --- tests/conftest.py | 4 +++- tests/test_pvpc.py | 17 ++++++++++++++--- tests/test_pvpc_parsing.py | 4 ++-- 3 files changed, 19 insertions(+), 6 deletions(-) diff --git a/tests/conftest.py b/tests/conftest.py index c4d3b12..536ceca 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -76,7 +76,9 @@ async def get(self, url, *_args, **_kwargs): and key in self.responses_esios ): self._raw_response = self.responses_esios[key] - elif url.startswith("https://apidatos.ree.es"): + elif ( + url.startswith("https://apidatos.ree.es") and key in self.responses_apidatos + ): self._raw_response = self.responses_apidatos[key] else: self._raw_response = _DEFAULT_EMPTY_VALUE diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index cee3858..f0ad89f 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -65,15 +65,26 @@ async def _run_h_step( # TODO review download schedule for Canary Islands TZ -@pytest.mark.parametrize("local_tz", (TZ_TEST, REFERENCE_TZ)) +@pytest.mark.parametrize( + "local_tz, source", + ( + (TZ_TEST, "apidatos"), + (REFERENCE_TZ, "apidatos"), + (TZ_TEST, "esios_public"), + (REFERENCE_TZ, "esios_public"), + ), +) @pytest.mark.asyncio -async def test_reduced_api_download_rate(local_tz): +async def test_reduced_api_download_rate(local_tz, source): """Test time evolution and number of API calls.""" start = datetime(2021, 10, 30, 15, tzinfo=UTC_TZ) mock_session = MockAsyncSession() # logging.critical(local_tz) pvpc_data = PVPCData( - websession=mock_session, tariff="2.0TD", local_timezone=local_tz + websession=mock_session, + tariff="2.0TD", + local_timezone=local_tz, + data_source=source, ) # avoid extra calls at day if already got all today prices diff --git a/tests/test_pvpc_parsing.py b/tests/test_pvpc_parsing.py index 3eecb57..22a4e5a 100644 --- a/tests/test_pvpc_parsing.py +++ b/tests/test_pvpc_parsing.py @@ -3,7 +3,7 @@ import pytest -from aiopvpc.const import REFERENCE_TZ, UTC_TZ +from aiopvpc.const import REFERENCE_TZ from aiopvpc.pvpc_data import PVPCData from tests.conftest import MockAsyncSession, TZ_TEST @@ -51,7 +51,7 @@ async def test_price_extract( available_8h, ): """Test data parsing of official API files.""" - day = datetime.fromisoformat(ts).astimezone(UTC_TZ) + day = datetime.fromisoformat(ts) mock_session = MockAsyncSession() pvpc_data = PVPCData( From 46f7f035f0c60cf9ec1fdcbbbfc0e47118ef7a70 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 12:36:50 +0100 Subject: [PATCH 08/13] :construction: Customize request headers for each data-source * Don't use User-Agent for apidatos.ree.es * Add Host + Content-Type headers --- aiopvpc/pvpc_data.py | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/aiopvpc/pvpc_data.py b/aiopvpc/pvpc_data.py index beab0b9..7981a18 100644 --- a/aiopvpc/pvpc_data.py +++ b/aiopvpc/pvpc_data.py @@ -92,10 +92,6 @@ def __init__( self._session = websession self._data_source = data_source self._user_agents = deque(sorted(_STANDARD_USER_AGENTS, key=lambda x: random())) - self._headers = { - "User-Agent": self._user_agents[0], - "Accept": "application/json", - } self._local_timezone = zoneinfo.ZoneInfo(str(local_timezone)) @@ -107,9 +103,23 @@ def __init__( _LOGGER.error("Unknown tariff '%s'. Should be one of %s", tariff, TARIFFS) self.tariff = TARIFFS[1] if zone_ceuta_melilla else TARIFFS[0] + def _request_headers(self) -> Dict[str, str]: + headers = { + "Accept": "application/json", + "Content-Type": "application/json", + } + if self._data_source == "apidatos": + headers["Host"] = "apidatos.ree.es" + return headers + headers["Host"] = "api.esios.ree.es" + headers["User-Agent"] = self._user_agents[0] + # TODO add auth token + # if self._data_source == "esios": + return headers + async def _api_get_prices(self, url: str, tariff: str) -> Dict[datetime, Any]: assert self._session is not None - resp = await self._session.get(url, headers=self._headers) + resp = await self._session.get(url, headers=self._request_headers()) if resp.status < 400: data = await resp.json() return extract_pvpc_data(data, url, tariff, tz=self._local_timezone) @@ -117,7 +127,6 @@ async def _api_get_prices(self, url: str, tariff: str) -> Dict[datetime, Any]: _LOGGER.warning("Forbidden error with '%s': %s", self._data_source, url) # loop user-agent and data-source self._user_agents.rotate() - self._headers["User-Agent"] = self._user_agents[0] self._data_source = ( "apidatos" if self._data_source == "esios_public" else "esios_public" ) From 8d796bd7dcc46bee4d646df1cb9db74eae8f4ddf Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 14:51:30 +0100 Subject: [PATCH 09/13] :bug: Add support to CYM prices in new data-source by setting `geo_ids=8744` in query params --- aiopvpc/const.py | 1 + aiopvpc/parser.py | 10 +++++++--- aiopvpc/pvpc_data.py | 7 +------ 3 files changed, 9 insertions(+), 9 deletions(-) diff --git a/aiopvpc/const.py b/aiopvpc/const.py index 02616eb..102b486 100644 --- a/aiopvpc/const.py +++ b/aiopvpc/const.py @@ -38,6 +38,7 @@ URL_APIDATOS_PRICES_RESOURCE = ( "https://apidatos.ree.es/es/datos/mercados/precios-mercados-tiempo-real" "?time_trunc=hour" + "&geo_ids={geo_id}" "&start_date={start:%Y-%m-%dT%H:%M}&end_date={end:%Y-%m-%dT%H:%M}" ) ATTRIBUTIONS: Dict[DataSource, str] = { diff --git a/aiopvpc/parser.py b/aiopvpc/parser.py index 42e160b..f0b6630 100644 --- a/aiopvpc/parser.py +++ b/aiopvpc/parser.py @@ -94,11 +94,15 @@ def extract_pvpc_data( return prices_data["series"]["PVPC"] -def get_url_prices(source: DataSource, now_local_ref: datetime) -> str: +def get_url_prices( + source: DataSource, zone_ceuta_melilla: bool, now_local_ref: datetime +) -> str: + """Make URL for PVPC prices.""" if source == "esios_public": return URL_PVPC_RESOURCE.format(day=now_local_ref.date()) start = now_local_ref.replace(hour=0, minute=0) end = now_local_ref.replace(hour=23, minute=59) - # TODO implement geo_zones!!! - return URL_APIDATOS_PRICES_RESOURCE.format(start=start, end=end) + return URL_APIDATOS_PRICES_RESOURCE.format( + start=start, end=end, geo_id=8744 if zone_ceuta_melilla else 8741 + ) diff --git a/aiopvpc/pvpc_data.py b/aiopvpc/pvpc_data.py index 7981a18..e44e363 100644 --- a/aiopvpc/pvpc_data.py +++ b/aiopvpc/pvpc_data.py @@ -62,14 +62,9 @@ class PVPCData: * Async download of prices for each day * Generate state attributes for HA integration. - * Async download of prices for a range of days - Prices are returned in a `Dict[datetime, float]`, with timestamps in UTC and prices in €/kWh. - - - Without a specific `tariff`, it would return the entire collection - of PVPC data, without any unit conversion, - and type `Dict[datetime, Dict[str, float]`. """ def __init__( @@ -145,7 +140,7 @@ async def _download_pvpc_prices(self, now: datetime) -> Dict[datetime, Any]: Prices are referenced with datetimes in UTC. """ assert now.date() >= DATE_CHANGE_TO_20TD, "No support for old tariffs" - url = get_url_prices(self._data_source, now) + url = get_url_prices(self._data_source, self._zone_ceuta_melilla, now) tariff = TARIFF2ID[self.tariff] try: async with async_timeout.timeout(2 * self.timeout): From 4f0c42aa12ceb98ba82552f3d7f61728cd1257d9 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 14:52:48 +0100 Subject: [PATCH 10/13] :white_check_mark: Add patterns and unit test for PCB/CYM prices --- .../PRICES_APIDATOS_2021_06_01_CYM.json | 154 ++++++++++++++++++ tests/conftest.py | 7 +- tests/test_pvpc.py | 1 - tests/test_pvpc_zones.py | 39 +++++ 4 files changed, 199 insertions(+), 2 deletions(-) create mode 100644 tests/api_examples/PRICES_APIDATOS_2021_06_01_CYM.json create mode 100644 tests/test_pvpc_zones.py diff --git a/tests/api_examples/PRICES_APIDATOS_2021_06_01_CYM.json b/tests/api_examples/PRICES_APIDATOS_2021_06_01_CYM.json new file mode 100644 index 0000000..3dff746 --- /dev/null +++ b/tests/api_examples/PRICES_APIDATOS_2021_06_01_CYM.json @@ -0,0 +1,154 @@ +{ + "data": { + "type": "Precios mercado peninsular en tiempo real", + "id": "mer13", + "attributes": { + "title": "Precios mercado peninsular en tiempo real", + "last-update": "2021-05-31T20:19:18.000+02:00", + "description": null + }, + "meta": { + "cache-control": { + "cache": "MISS" + } + } + }, + "included": [ + { + "type": "PVPC (\u20ac\/MWh)", + "id": "1001", + "groupId": null, + "attributes": { + "title": "PVPC (\u20ac\/MWh)", + "description": null, + "color": "#ffcf09", + "type": null, + "magnitude": "price", + "composite": false, + "last-update": "2021-05-31T20:19:18.000+02:00", + "values": [ + { + "value": 116.33, + "percentage": 1, + "datetime": "2021-06-01T00:00:00.000+02:00" + }, + { + "value": 115.95, + "percentage": 1, + "datetime": "2021-06-01T01:00:00.000+02:00" + }, + { + "value": 114.89, + "percentage": 1, + "datetime": "2021-06-01T02:00:00.000+02:00" + }, + { + "value": 114.96, + "percentage": 1, + "datetime": "2021-06-01T03:00:00.000+02:00" + }, + { + "value": 114.84, + "percentage": 1, + "datetime": "2021-06-01T04:00:00.000+02:00" + }, + { + "value": 116.03, + "percentage": 1, + "datetime": "2021-06-01T05:00:00.000+02:00" + }, + { + "value": 116.29, + "percentage": 1, + "datetime": "2021-06-01T06:00:00.000+02:00" + }, + { + "value": 115.7, + "percentage": 1, + "datetime": "2021-06-01T07:00:00.000+02:00" + }, + { + "value": 152.89, + "percentage": 1, + "datetime": "2021-06-01T08:00:00.000+02:00" + }, + { + "value": 150.83, + "percentage": 1, + "datetime": "2021-06-01T09:00:00.000+02:00" + }, + { + "value": 149.28, + "percentage": 1, + "datetime": "2021-06-01T10:00:00.000+02:00" + }, + { + "value": 240.5, + "percentage": 1, + "datetime": "2021-06-01T11:00:00.000+02:00" + }, + { + "value": 238.09, + "percentage": 1, + "datetime": "2021-06-01T12:00:00.000+02:00" + }, + { + "value": 235.3, + "percentage": 1, + "datetime": "2021-06-01T13:00:00.000+02:00" + }, + { + "value": 231.28, + "percentage": 1, + "datetime": "2021-06-01T14:00:00.000+02:00" + }, + { + "value": 132.88, + "percentage": 1, + "datetime": "2021-06-01T15:00:00.000+02:00" + }, + { + "value": 131.93, + "percentage": 1, + "datetime": "2021-06-01T16:00:00.000+02:00" + }, + { + "value": 135.99, + "percentage": 1, + "datetime": "2021-06-01T17:00:00.000+02:00" + }, + { + "value": 138.13, + "percentage": 1, + "datetime": "2021-06-01T18:00:00.000+02:00" + }, + { + "value": 240.4, + "percentage": 1, + "datetime": "2021-06-01T19:00:00.000+02:00" + }, + { + "value": 246.2, + "percentage": 1, + "datetime": "2021-06-01T20:00:00.000+02:00" + }, + { + "value": 248.08, + "percentage": 1, + "datetime": "2021-06-01T21:00:00.000+02:00" + }, + { + "value": 249.41, + "percentage": 1, + "datetime": "2021-06-01T22:00:00.000+02:00" + }, + { + "value": 156.5, + "percentage": 1, + "datetime": "2021-06-01T23:00:00.000+02:00" + } + ] + } + } + ] +} diff --git a/tests/conftest.py b/tests/conftest.py index 536ceca..d05619a 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -17,6 +17,7 @@ FIXTURE_JSON_DATA_2022_03_27 = "PVPC_CURV_DD_2022_03_27.json" FIXTURE_JSON_DATA_2021_06_01 = "PVPC_CURV_DD_2021_06_01.json" FIXTURE_JSON_DATA_S2_2021_06_01 = "PRICES_APIDATOS_2021_06_01.json" +FIXTURE_JSON_DATA_S2_2021_06_01_CYM = "PRICES_APIDATOS_2021_06_01_CYM.json" FIXTURE_JSON_DATA_S2_2021_10_30 = "PRICES_APIDATOS_2021_10_30.json" FIXTURE_JSON_DATA_S2_2021_10_31 = "PRICES_APIDATOS_2021_10_31.json" @@ -50,6 +51,7 @@ def __init__(self, status=200, exc=None): self.exc = exc self.responses_apidatos = { + "CYM_PRICES": load_fixture(FIXTURE_JSON_DATA_S2_2021_06_01_CYM), date(2021, 10, 30): load_fixture(FIXTURE_JSON_DATA_S2_2021_10_30), date(2021, 10, 31): load_fixture(FIXTURE_JSON_DATA_S2_2021_10_31), date(2021, 6, 1): load_fixture(FIXTURE_JSON_DATA_S2_2021_06_01), @@ -71,7 +73,10 @@ async def get(self, url, *_args, **_kwargs): if self.exc: raise self.exc key = datetime.fromisoformat(url.split("=")[-1]).date() - if ( + if key == date(2021, 6, 1) and "geo_ids=8744" in url: + assert url.startswith("https://apidatos.ree.es") + self._raw_response = self.responses_apidatos["CYM_PRICES"] + elif ( url.startswith("https://api.esios.ree.es/archives") and key in self.responses_esios ): diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index f0ad89f..5a64d5a 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -79,7 +79,6 @@ async def test_reduced_api_download_rate(local_tz, source): """Test time evolution and number of API calls.""" start = datetime(2021, 10, 30, 15, tzinfo=UTC_TZ) mock_session = MockAsyncSession() - # logging.critical(local_tz) pvpc_data = PVPCData( websession=mock_session, tariff="2.0TD", diff --git a/tests/test_pvpc_zones.py b/tests/test_pvpc_zones.py new file mode 100644 index 0000000..2657d37 --- /dev/null +++ b/tests/test_pvpc_zones.py @@ -0,0 +1,39 @@ +"""Tests for aiopvpc.""" +from datetime import datetime + +import pytest + +from aiopvpc.const import REFERENCE_TZ, UTC_TZ +from aiopvpc.pvpc_data import PVPCData +from tests.conftest import MockAsyncSession, TZ_TEST + + +@pytest.mark.parametrize( + "local_tz, source, zone_ceuta_melilla, expected_18h", + ( + (TZ_TEST, "apidatos", False, 0.23144), + (REFERENCE_TZ, "apidatos", False, 0.23144), + (REFERENCE_TZ, "apidatos", True, 0.13813), + (TZ_TEST, "esios_public", False, 0.23144), + (REFERENCE_TZ, "esios_public", False, 0.23144), + (REFERENCE_TZ, "esios_public", True, 0.13813), + ), +) +@pytest.mark.asyncio +async def test_geo_ids(local_tz, source, zone_ceuta_melilla, expected_18h): + """Test different prices for different geo zones.""" + start = datetime(2021, 6, 1, 10, tzinfo=UTC_TZ) + mock_session = MockAsyncSession() + pvpc_data = PVPCData( + websession=mock_session, + zone_ceuta_melilla=zone_ceuta_melilla, + local_timezone=local_tz, + data_source=source, + ) + await pvpc_data.async_update_prices(start) + assert pvpc_data.process_state_and_attributes(start) + # for ts, price in pvpc_data._current_prices.items(): + # print(f"{ts.astimezone(local_tz):%H}h --> {price:.5f} ") + ts_loc_18h_utc = datetime(2021, 6, 1, 18, tzinfo=local_tz).astimezone(UTC_TZ) + price_loc_18h = pvpc_data._current_prices[ts_loc_18h_utc] + assert price_loc_18h == expected_18h From 4f023de2716d28012551f8c8386ddb2007cfd860 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 15:08:27 +0100 Subject: [PATCH 11/13] :construction: Minor refactor for PVPCData parameters --- README.md | 2 +- aiopvpc/pvpc_data.py | 20 ++++++++++---------- tests/test_pvpc.py | 4 ++-- tests/test_pvpc_parsing.py | 3 +-- tests/test_pvpc_zones.py | 22 +++++++++++----------- tests/test_real_api_calls.py | 4 ++-- 6 files changed, 27 insertions(+), 28 deletions(-) diff --git a/README.md b/README.md index 3f4e97b..2f92fd0 100644 --- a/README.md +++ b/README.md @@ -33,7 +33,7 @@ from datetime import datetime from aiopvpc import PVPCData async with aiohttp.ClientSession() as session: - pvpc_handler = PVPCData(websession=session, tariff="2.0TD") + pvpc_handler = PVPCData(session=session, tariff="2.0TD") prices: dict = await pvpc_handler.async_update_prices(datetime.utcnow()) print(prices) ``` diff --git a/aiopvpc/pvpc_data.py b/aiopvpc/pvpc_data.py index e44e363..63e9e53 100644 --- a/aiopvpc/pvpc_data.py +++ b/aiopvpc/pvpc_data.py @@ -69,10 +69,10 @@ class PVPCData: def __init__( self, - websession: aiohttp.ClientSession, - tariff: str, + *, + session: aiohttp.ClientSession, + tariff: str = TARIFFS[0], local_timezone: Union[str, zoneinfo.ZoneInfo] = REFERENCE_TZ, - zone_ceuta_melilla: bool = False, power: float = DEFAULT_POWER_KW, power_valley: float = DEFAULT_POWER_KW, timeout: float = DEFAULT_TIMEOUT, @@ -84,19 +84,19 @@ def __init__( self.attributes: Dict[str, Any] = {} self.timeout = timeout - self._session = websession + self._session = session self._data_source = data_source self._user_agents = deque(sorted(_STANDARD_USER_AGENTS, key=lambda x: random())) self._local_timezone = zoneinfo.ZoneInfo(str(local_timezone)) + self.tariff = tariff + if tariff not in TARIFFS: # pragma: no cover + _LOGGER.error("Unknown tariff '%s'. Should be one of %s", tariff, TARIFFS) + self.tariff = TARIFFS[0] self._current_prices: Dict[datetime, float] = {} self._power = power self._power_valley = power_valley - self._zone_ceuta_melilla = zone_ceuta_melilla - if tariff not in TARIFFS: # pragma: no cover - _LOGGER.error("Unknown tariff '%s'. Should be one of %s", tariff, TARIFFS) - self.tariff = TARIFFS[1] if zone_ceuta_melilla else TARIFFS[0] def _request_headers(self) -> Dict[str, str]: headers = { @@ -140,7 +140,7 @@ async def _download_pvpc_prices(self, now: datetime) -> Dict[datetime, Any]: Prices are referenced with datetimes in UTC. """ assert now.date() >= DATE_CHANGE_TO_20TD, "No support for old tariffs" - url = get_url_prices(self._data_source, self._zone_ceuta_melilla, now) + url = get_url_prices(self._data_source, self.tariff != TARIFFS[0], now) tariff = TARIFF2ID[self.tariff] try: async with async_timeout.timeout(2 * self.timeout): @@ -283,7 +283,7 @@ def process_state_and_attributes(self, utc_now: datetime) -> bool: # generate PVPC 2.0TD sensor attributes local_time = utc_time.astimezone(self._local_timezone) (current_period, next_period, delta,) = get_current_and_next_tariff_periods( - local_time, zone_ceuta_melilla=self._zone_ceuta_melilla + local_time, zone_ceuta_melilla=self.tariff != TARIFFS[0] ) attributes["period"] = current_period power = self._power_valley if current_period == "P3" else self._power diff --git a/tests/test_pvpc.py b/tests/test_pvpc.py index 5a64d5a..65cddce 100644 --- a/tests/test_pvpc.py +++ b/tests/test_pvpc.py @@ -35,7 +35,7 @@ async def test_bad_downloads( day = datetime.fromisoformat(day_str).astimezone(REFERENCE_TZ) mock_session = MockAsyncSession(status=status, exc=exception) with caplog.at_level(logging.INFO): - pvpc_data = PVPCData(websession=mock_session, tariff="2.0TD") + pvpc_data = PVPCData(session=mock_session, tariff="2.0TD") pvpc_data.source_available = available assert not pvpc_data.process_state_and_attributes(day) prices = await pvpc_data.async_update_prices(day) @@ -80,7 +80,7 @@ async def test_reduced_api_download_rate(local_tz, source): start = datetime(2021, 10, 30, 15, tzinfo=UTC_TZ) mock_session = MockAsyncSession() pvpc_data = PVPCData( - websession=mock_session, + session=mock_session, tariff="2.0TD", local_timezone=local_tz, data_source=source, diff --git a/tests/test_pvpc_parsing.py b/tests/test_pvpc_parsing.py index 22a4e5a..89a71aa 100644 --- a/tests/test_pvpc_parsing.py +++ b/tests/test_pvpc_parsing.py @@ -55,10 +55,9 @@ async def test_price_extract( mock_session = MockAsyncSession() pvpc_data = PVPCData( + session=mock_session, tariff="2.0TD", local_timezone=timezone, - websession=mock_session, - zone_ceuta_melilla=zone_cm, data_source=source, ) diff --git a/tests/test_pvpc_zones.py b/tests/test_pvpc_zones.py index 2657d37..07c61a6 100644 --- a/tests/test_pvpc_zones.py +++ b/tests/test_pvpc_zones.py @@ -3,30 +3,30 @@ import pytest -from aiopvpc.const import REFERENCE_TZ, UTC_TZ +from aiopvpc.const import REFERENCE_TZ, TARIFFS, UTC_TZ from aiopvpc.pvpc_data import PVPCData from tests.conftest import MockAsyncSession, TZ_TEST @pytest.mark.parametrize( - "local_tz, source, zone_ceuta_melilla, expected_18h", + "local_tz, source, tariff, expected_18h", ( - (TZ_TEST, "apidatos", False, 0.23144), - (REFERENCE_TZ, "apidatos", False, 0.23144), - (REFERENCE_TZ, "apidatos", True, 0.13813), - (TZ_TEST, "esios_public", False, 0.23144), - (REFERENCE_TZ, "esios_public", False, 0.23144), - (REFERENCE_TZ, "esios_public", True, 0.13813), + (TZ_TEST, "apidatos", TARIFFS[0], 0.23144), + (REFERENCE_TZ, "apidatos", TARIFFS[0], 0.23144), + (REFERENCE_TZ, "apidatos", TARIFFS[1], 0.13813), + (TZ_TEST, "esios_public", TARIFFS[0], 0.23144), + (REFERENCE_TZ, "esios_public", TARIFFS[0], 0.23144), + (REFERENCE_TZ, "esios_public", TARIFFS[1], 0.13813), ), ) @pytest.mark.asyncio -async def test_geo_ids(local_tz, source, zone_ceuta_melilla, expected_18h): +async def test_geo_ids(local_tz, source, tariff, expected_18h): """Test different prices for different geo zones.""" start = datetime(2021, 6, 1, 10, tzinfo=UTC_TZ) mock_session = MockAsyncSession() pvpc_data = PVPCData( - websession=mock_session, - zone_ceuta_melilla=zone_ceuta_melilla, + session=mock_session, + tariff=tariff, local_timezone=local_tz, data_source=source, ) diff --git a/tests/test_real_api_calls.py b/tests/test_real_api_calls.py index 2011e8d..a66709f 100644 --- a/tests/test_real_api_calls.py +++ b/tests/test_real_api_calls.py @@ -23,10 +23,10 @@ async def test_real_download_today_async(data_source, tz): async with ClientSession() as session: pvpc_handler = PVPCData( - websession=session, + session=session, tariff="2.0TD", - data_source=data_source, local_timezone=tz, + data_source=data_source, ) prices = await pvpc_handler.async_update_prices(datetime.utcnow()) assert 22 < len(prices) < 49 From 3900d8218bc8b004f72dbf91d50f03beadfce668 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Sun, 5 Dec 2021 15:21:04 +0100 Subject: [PATCH 12/13] :art: Update pre-commit config --- .pre-commit-config.yaml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index dfc4b90..43c4bf5 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,14 +1,14 @@ minimum_pre_commit_version: "2.10.0" repos: - repo: https://github.com/pycqa/isort - rev: 5.8.0 + rev: 5.10.1 hooks: - id: isort name: isort (python) args: - --dont-order-by-type - repo: https://github.com/psf/black - rev: "21.6b0" + rev: "21.11b1" hooks: - id: black name: Format code (black) @@ -21,7 +21,7 @@ repos: - id: check-toml - id: check-yaml - repo: https://github.com/pycqa/flake8 - rev: "3.9.2" + rev: "4.0.1" hooks: - id: flake8 name: Lint code (flake8) @@ -39,7 +39,7 @@ repos: - flake8-variables-names>=0.0.3 - pep8-naming>=0.11.1 - repo: "https://github.com/pre-commit/mirrors-mypy" - rev: "v0.902" + rev: "v0.910-1" hooks: - id: "mypy" name: "Check type hints (mypy)" From 611bb41b7f8b43071ceec84d9e734062887a0395 Mon Sep 17 00:00:00 2001 From: Eugenio Panadero Date: Mon, 20 Dec 2021 14:08:21 +0100 Subject: [PATCH 13/13] :rocket: Bump major version to 3.0.0 * Remove example notebook and extra deps * Update CHANGELOG.md --- CHANGELOG.md | 33 + Notebooks/Download PVPC prices.ipynb | 1237 --------------------- Notebooks/sample_pvpc_plot.png | Bin 91050 -> 0 bytes README.md | 5 - poetry.lock | 1546 +------------------------- pyproject.toml | 9 +- 6 files changed, 46 insertions(+), 2784 deletions(-) delete mode 100644 Notebooks/Download PVPC prices.ipynb delete mode 100644 Notebooks/sample_pvpc_plot.png diff --git a/CHANGELOG.md b/CHANGELOG.md index 60265cc..2d34ff7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,38 @@ # Changelog +## [v3.0.0](https://github.com/azogue/aiopvpc/tree/v3.0.0) - Change Data Source to apidatos.ree.es (2021-12-05) + +[Full Changelog](https://github.com/azogue/aiopvpc/compare/v3.0.0...v2.3.0) + +🔥 **BREAKING-CHANGE**: this release **removes support for the old PVPC tariffs** +(prices < 2021-06-01), and the extra methods to use this library as a _dataloader_ +(`.download_prices_for_range(...)`), leaving only the **code to support the HA Core integration**. + +Motivated by recent successful attempts to kick us out from `api.esios.ree.es`, +we are changing the data source to another REE public server, at `apidatos.ree.es`, +with the same information than the current one, available without authentication 👌 + +**This release implements the new data-source**, but also maintains the _legacy_ one. + +* Initial configuration is set with a new `data_source` parameter, **with the new source as default**. +* If a 403 status-code is received, the **data source is switched** (new to legacy / legacy to new), no retry is done, + and the User-Agent loop trick is only used for the legacy data-source. + +**Changes:** + +* :fire: Remove support for old PVPC tariffs and range download methods, +and make `tariff` and `websession` required arguments + +* :sparkles: Add alternative data-source from 'apidatos.ree.es' + * Implement data parsing from `apidatos.ree.es`, using endpoint at `/es/datos/mercados/precios-mercados-tiempo-real` + * Add `data_source` parameter with valid keys 'apidatos' and 'esios_public', setting the new one as default ;-) + * Remove retry call if 403 status is received, but maintain the User-Agent loop, and also toggle the data-source for the next call + * Move old ATTRIBUTION to `.attribution` property, as function of the data-source + +* :truck: Change test patterns to new tariffs by substituting old examples in DST days from 2019 to equivalent days since 2021-06, using the new tariff keys + +* :truck: Add test patterns from new data-source, and adjust tests + ## [v2.3.0](https://github.com/azogue/aiopvpc/tree/v2.3.0) - Decrease API refresh rate and try to avoid banning (2021-12-01) [Full Changelog](https://github.com/azogue/aiopvpc/compare/v2.3.0...v2.2.4) diff --git a/Notebooks/Download PVPC prices.ipynb b/Notebooks/Download PVPC prices.ipynb deleted file mode 100644 index 9644d0d..0000000 --- a/Notebooks/Download PVPC prices.ipynb +++ /dev/null @@ -1,1237 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Download PVPC prices for a time range with `aiopvpc`\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Download of 883 prices from 2021-05-01 20:00:00+00:00 to 2021-06-07 14:00:00+00:00 in 0.16 sec\n" - ] - }, - { - "data": { - "text/plain": [ - "[(datetime.datetime(2021, 5, 1, 20, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.1708),\n", - " (datetime.datetime(2021, 5, 1, 21, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.09135),\n", - " (datetime.datetime(2021, 5, 1, 22, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08392),\n", - " (datetime.datetime(2021, 5, 1, 23, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08088),\n", - " (datetime.datetime(2021, 5, 2, 0, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.0818),\n", - " (datetime.datetime(2021, 5, 2, 1, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08288),\n", - " (datetime.datetime(2021, 5, 2, 2, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08327),\n", - " (datetime.datetime(2021, 5, 2, 3, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08336),\n", - " (datetime.datetime(2021, 5, 2, 4, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.08684),\n", - " (datetime.datetime(2021, 5, 2, 5, 0, tzinfo=zoneinfo.ZoneInfo(key='UTC')),\n", - " 0.0833)]" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from datetime import datetime\n", - "\n", - "from aiopvpc.pvpc_data import PVPCData, REFERENCE_TZ\n", - "\n", - "# Initialize PVPC handler\n", - "pvpc_handler = PVPCData(tariff=\"discrimination\", zone_ceuta_melilla=False)\n", - "\n", - "# download prices in range\n", - "start = datetime(2021, 5, 1, 22, tzinfo=REFERENCE_TZ)\n", - "end = datetime(2021, 6, 7, 16, tzinfo=REFERENCE_TZ)\n", - "\n", - "prices_range: dict = await pvpc_handler.async_download_prices_for_range(start, end)\n", - "\n", - "# show first values\n", - "list(prices_range.items())[:10]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plot PVPC prices with `pandas` and `matplotlib`\n", - "\n", - "* Convert dict of downloaded prices to pd.Series\n", - "* Plot series as step graph with filled area" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "%config InlineBackend.figure_format = 'retina'\n", - "\n", - "import matplotlib.dates as mdates\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "\n", - "\n", - "# plot series as filled step graph\n", - "def plot_data(\n", - " s_data: pd.Series,\n", - " ylabel: str = \"Consumo (kWh)\",\n", - " color = \"xkcd:orangey red\",\n", - " figsize = (16, 7),\n", - " tz = REFERENCE_TZ,\n", - " fill_under: bool = True,\n", - " title: str = None,\n", - " plot_style: str = \"seaborn-white\",\n", - " date_fmt: str = \"%-d/%b\\'%y\",\n", - " max_xticks: int = 10,\n", - " ax = None,\n", - "):\n", - " plt.style.use(plot_style)\n", - " # Use local naive time index\n", - " index_plot = s_data.index.tz_convert(str(tz)).tz_localize(None)\n", - " ts0 = index_plot[0]\n", - " tsf = index_plot[-1]\n", - "\n", - " # add 1 more point for final \"step\"\n", - " delta_step = tsf - index_plot[-2]\n", - " tsf += delta_step\n", - " \n", - " index_p = index_plot.tolist() + [tsf]\n", - " values_p = s_data.values.tolist() + [s_data.values[-1]]\n", - "\n", - " # get figure params\n", - " fig_p = {\"ax\": ax} if ax is not None else {\"figure\": plt.figure(figsize=figsize)}\n", - " \n", - " # plot values as step\n", - " line, *_ = plt.step(\n", - " index_p, values_p,\n", - " where=\"post\",\n", - " lw=0.75, ls=\"-\", alpha=.95, marker=None, color=color,\n", - " label=ylabel,\n", - " **fig_p,\n", - " )\n", - "\n", - " # fill under line\n", - " if fill_under:\n", - " xy_line = line.get_xydata()\n", - " plt.fill_between(\n", - " xy_line[:, 0], xy_line[:, 1], color=color, step=\"post\", alpha=.3\n", - " )\n", - "\n", - " # style plot\n", - " ax = plt.gca()\n", - " ax.xaxis.set_major_formatter(mdates.DateFormatter(date_fmt))\n", - " ax.xaxis.set_major_locator(mdates.DayLocator(interval=(tsf - ts0).days // max_xticks + 1))\n", - " ax.grid(True, which=\"both\", axis=\"both\")\n", - " ax.set_xlim(ts0, tsf)\n", - " ax.set_ylim(0, ax.get_ylim()[1])\n", - " ax.set_ylabel(ylabel, usetex=True)\n", - " \n", - " if title is not None:\n", - " ax.set_title(title)\n", - " \n", - " return ax\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "2021-05-01 20:00:00+00:00 0.17080\n", - "2021-05-01 21:00:00+00:00 0.09135\n", - "2021-05-01 22:00:00+00:00 0.08392\n", - "2021-05-01 23:00:00+00:00 0.08088\n", - "2021-05-02 00:00:00+00:00 0.08180\n", - " ... \n", - "2021-06-07 10:00:00+00:00 0.23198\n", - "2021-06-07 11:00:00+00:00 0.23150\n", - "2021-06-07 12:00:00+00:00 0.13706\n", - "2021-06-07 13:00:00+00:00 0.13554\n", - "2021-06-07 14:00:00+00:00 0.13540\n", - "Name: price_€_kWh, Length: 883, dtype: float64" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "image/png": { - "height": 422, - "width": 945 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "# move to pandas to plot series\n", - "s_price_example = pd.Series(prices_range, name=\"price_€_kWh\")\n", - "display(s_price_example)\n", - "\n", - "# plot prices\n", - "plot_data(\n", - " s_price_example, \"PVPC (€/kWh)\", \"xkcd:cerulean blue\",\n", - " figsize=(16, 7),\n", - " tz=REFERENCE_TZ,\n", - " fill_under=True,\n", - " plot_style=\"seaborn-white\",\n", - " date_fmt=\"%-d/%b\\'%y\",\n", - " max_xticks=10,\n", - " title=\"PVPC (discriminación -> 2.0TD)\",\n", - ")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Download full PVPC detailed data in €/MWh\n", - "\n", - "By not using a specific `tariff` in the `PVPCData` handler" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Collecting detailed PVPC data for all tariffs\n", - "Download of 978 prices from 2020-03-20 23:00:00+00:00 to 2020-04-30 16:00:00+00:00 in 0.33 sec\n" - ] - }, - { - "data": { - "text/plain": [ - "{'GEN': 86.42,\n", - " 'NOC': 38.19,\n", - " 'VHC': 41.04,\n", - " 'COFGEN': 9.8155543e-05,\n", - " 'COFNOC': 0.000149140796,\n", - " 'COFVHC': 0.000144086677,\n", - " 'PMHGEN': 31.35,\n", - " 'PMHNOC': 29.97,\n", - " 'PMHVHC': 31.5,\n", - " 'SAHGEN': 3.51,\n", - " 'SAHNOC': 3.35,\n", - " 'SAHVHC': 3.53,\n", - " 'FOMGEN': 0.03,\n", - " 'FOMNOC': 0.03,\n", - " 'FOMVHC': 0.03,\n", - " 'FOSGEN': 0.17,\n", - " 'FOSNOC': 0.16,\n", - " 'FOSVHC': 0.17,\n", - " 'INTGEN': 0.04,\n", - " 'INTNOC': 0.04,\n", - " 'INTVHC': 0.04,\n", - " 'PCAPGEN': 5.68,\n", - " 'PCAPNOC': 0.94,\n", - " 'PCAPVHC': 1.34,\n", - " 'TEUGEN': 44.03,\n", - " 'TEUNOC': 2.22,\n", - " 'TEUVHC': 2.88,\n", - " 'CCVGEN': 1.61,\n", - " 'CCVNOC': 1.47,\n", - " 'CCVVHC': 1.55}" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "full_pvpc_handler = PVPCData()\n", - "\n", - "# download prices in range\n", - "start = datetime(2020, 3, 21)\n", - "end = datetime(2020, 4, 30, 18)\n", - "\n", - "prices_data: dict = await full_pvpc_handler.async_download_prices_for_range(start, end)\n", - "\n", - "# Example of detailed data\n", - "prices_data[min(prices_data)]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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GENNOCVHCCOFGENCOFNOCCOFVHCPMHGENPMHNOCPMHVHCSAHGEN...INTVHCPCAPGENPCAPNOCPCAPVHCTEUGENTEUNOCTEUVHCCCVGENCCVNOCCCVVHC
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2020-03-21 00:00:00+00:0083.7335.5733.060.0000790.0001320.00016228.0426.7925.994.13...0.035.710.950.7444.032.220.891.581.441.39
2020-03-21 01:00:00+00:0087.2638.9036.270.0000680.0001200.00015931.6130.1829.264.01...0.035.740.950.7444.032.220.891.641.491.45
2020-03-21 02:00:00+00:0087.9339.5036.820.0000620.0001120.00015231.6730.2229.274.60...0.035.750.950.7444.032.220.891.651.501.45
2020-03-21 03:00:00+00:0088.5340.0737.400.0000600.0001100.00014532.2930.8129.874.56...0.035.750.950.7444.032.220.891.661.511.46
..................................................................
2020-04-30 12:00:00+00:0060.7579.0179.010.0001250.0000850.0000726.356.396.393.63...0.055.335.535.5344.0362.0162.011.181.191.19
2020-04-30 13:00:00+00:0061.1679.4479.440.0001160.0000780.0000686.416.466.463.95...0.055.365.565.5644.0362.0162.011.181.201.20
2020-04-30 14:00:00+00:0061.1479.4379.430.0001110.0000740.0000666.406.456.453.95...0.055.355.555.5544.0362.0162.011.181.191.19
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" - ], - "text/plain": [ - " NOC PMHNOC SAHNOC FOMNOC FOSNOC INTNOC \\\n", - "2020-03-20 23:00:00+00:00 38.19 29.97 3.35 0.03 0.16 0.04 \n", - "2020-03-21 00:00:00+00:00 35.57 26.79 3.95 0.03 0.16 0.04 \n", - "2020-03-21 01:00:00+00:00 38.90 30.18 3.83 0.03 0.16 0.04 \n", - "2020-03-21 02:00:00+00:00 39.50 30.22 4.38 0.03 0.16 0.04 \n", - "2020-03-21 03:00:00+00:00 40.07 30.81 4.35 0.03 0.16 0.04 \n", - "... ... ... ... ... ... ... \n", - "2020-03-24 18:00:00+00:00 110.67 39.12 2.14 0.03 0.16 0.03 \n", - "2020-03-24 19:00:00+00:00 111.02 39.71 1.84 0.03 0.16 0.03 \n", - "2020-03-24 20:00:00+00:00 110.88 39.35 2.04 0.03 0.16 0.04 \n", - "2020-03-24 21:00:00+00:00 42.79 35.55 2.36 0.03 0.16 0.03 \n", - "2020-03-24 22:00:00+00:00 41.95 34.41 2.67 0.03 0.16 0.03 \n", - "\n", - " PCAPNOC TEUNOC CCVNOC \n", - "2020-03-20 23:00:00+00:00 0.94 2.22 1.47 \n", - "2020-03-21 00:00:00+00:00 0.95 2.22 1.44 \n", - "2020-03-21 01:00:00+00:00 0.95 2.22 1.49 \n", - "2020-03-21 02:00:00+00:00 0.95 2.22 1.50 \n", - "2020-03-21 03:00:00+00:00 0.95 2.22 1.51 \n", - "... ... ... ... \n", - "2020-03-24 18:00:00+00:00 5.52 62.01 1.65 \n", - "2020-03-24 19:00:00+00:00 5.56 62.01 1.66 \n", - "2020-03-24 20:00:00+00:00 5.59 62.01 1.67 \n", - "2020-03-24 21:00:00+00:00 0.92 2.22 1.52 \n", - "2020-03-24 22:00:00+00:00 0.92 2.22 1.51 \n", - "\n", - "[96 rows x 9 columns]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 701, - "width": 1150 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "# show some details\n", - "subset_noc = df_pvpc.iloc[:96].T[df_pvpc.columns.str.endswith(\"NOC\")].drop(\"COFNOC\").T\n", - "display(subset_noc)\n", - "\n", - "subset_noc.plot(figsize=(20, 12));" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Download of 145 prices from 2021-05-31 22:00:00+00:00 to 2021-06-06 22:00:00+00:00 in 1.21 sec\n" - ] - }, - { - "data": { - "text/plain": [ - "{'PCB': 116.33,\n", - " 'CYM': 116.33,\n", - " 'COF2TD': 8.8075182e-05,\n", - " 'PMHPCB': 104.0,\n", - " 'PMHCYM': 104.0,\n", - " 'SAHPCB': 3.56,\n", - " 'SAHCYM': 3.56,\n", - " 'FOMPCB': 0.03,\n", - " 'FOMCYM': 0.03,\n", - " 'FOSPCB': 0.17,\n", - " 'FOSCYM': 0.17,\n", - " 'INTPCB': 0.0,\n", - " 'INTCYM': 0.0,\n", - " 'PCAPPCB': 0.0,\n", - " 'PCAPCYM': 0.0,\n", - " 'TEUPCB': 6.0,\n", - " 'TEUCYM': 6.0,\n", - " 'CCVPCB': 2.57,\n", - " 'CCVCYM': 2.57,\n", - " 'EDSRPCB': 0.0,\n", - " 'EDSRCYM': 0.0}" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# download prices in range\n", - "start = datetime(2021, 6, 1)\n", - "end = datetime(2021, 6, 7)\n", - "\n", - "prices_data: dict = await full_pvpc_handler.async_download_prices_for_range(start, end)\n", - "\n", - "# Example of detailed data\n", - "prices_data[min(prices_data)]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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2021-05-31 22:00:00+00:00116.33104.003.560.030.170.00.006.002.570.0
2021-05-31 23:00:00+00:00115.95103.183.990.030.170.00.006.002.580.0
2021-06-01 00:00:00+00:00114.89101.874.250.030.170.00.006.002.560.0
2021-06-01 01:00:00+00:00114.96102.014.190.030.170.00.006.002.570.0
2021-06-01 02:00:00+00:00114.84101.874.210.030.170.00.006.002.560.0
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2021-06-04 17:00:00+00:00236.5893.834.930.030.170.02.04133.122.460.0
2021-06-04 18:00:00+00:00238.3294.465.990.030.170.02.06133.122.490.0
2021-06-04 19:00:00+00:00239.3996.534.960.030.170.02.07133.122.510.0
2021-06-04 20:00:00+00:00144.4294.325.310.030.170.00.3541.772.470.0
2021-06-04 21:00:00+00:00140.6588.847.070.030.170.00.3541.772.420.0
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- "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 701, - "width": 1150 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "# show some details\n", - "df_pvpc = pd.DataFrame(prices_data).T\n", - "subset_noc = df_pvpc.iloc[:96].T[df_pvpc.columns.str.endswith(\"PCB\")].T\n", - "display(subset_noc)\n", - "\n", - "subset_noc.plot(figsize=(20, 12));" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Notebooks/sample_pvpc_plot.png b/Notebooks/sample_pvpc_plot.png deleted file mode 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a/README.md +++ b/README.md @@ -37,8 +37,3 @@ async with aiohttp.ClientSession() as session: prices: dict = await pvpc_handler.async_update_prices(datetime.utcnow()) print(prices) ``` - -Check [this example on a jupyter notebook](https://github.com/azogue/aiopvpc/blob/master/Notebooks/Download%20PVPC%20prices.ipynb), where the downloader is combined with pandas and matplotlib to plot the electricity prices. -To play with it, clone the repo and install the project with `poetry install -E jupyter`, and then `poetry run jupyter notebook`. - -![sample_pvpc_plot.png](https://github.com/azogue/aiopvpc/blob/master/Notebooks/sample_pvpc_plot.png) diff --git a/poetry.lock b/poetry.lock index 426dd0c..7e7d2f6 100644 --- a/poetry.lock +++ b/poetry.lock @@ -29,30 +29,6 @@ python-versions = ">=3.6" [package.dependencies] frozenlist = ">=1.1.0" -[[package]] -name = "appnope" -version = "0.1.2" -description = "Disable App Nap on macOS >= 10.9" -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "argon2-cffi" -version = "21.1.0" -description = "The secure Argon2 password hashing algorithm." -category = "main" -optional = true -python-versions = ">=3.5" - -[package.dependencies] -cffi = ">=1.0.0" - -[package.extras] -dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "furo", "wheel", "pre-commit"] -docs = ["sphinx", "furo"] -tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] - [[package]] name = "async-timeout" version = "4.0.1" @@ -86,14 +62,6 @@ docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"] tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"] -[[package]] -name = "backcall" -version = "0.2.0" -description = "Specifications for callback functions passed in to an API" -category = "main" -optional = true -python-versions = "*" - [[package]] name = "backports.entry-points-selectable" version = "1.1.1" @@ -119,7 +87,7 @@ tzdata = ["tzdata"] [[package]] name = "black" -version = "21.11b1" +version = "21.12b0" description = "The uncompromising code formatter." category = "dev" optional = false @@ -130,7 +98,6 @@ click = ">=7.1.2" mypy-extensions = ">=0.4.3" pathspec = ">=0.9.0,<1" platformdirs = ">=2" -regex = ">=2021.4.4" tomli = ">=0.2.6,<2.0.0" typing-extensions = [ {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}, @@ -144,30 +111,6 @@ jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] python2 = ["typed-ast (>=1.4.3)"] uvloop = ["uvloop (>=0.15.2)"] -[[package]] -name = "bleach" -version = "4.1.0" -description = "An easy safelist-based HTML-sanitizing tool." -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -packaging = "*" -six = ">=1.9.0" -webencodings = "*" - -[[package]] -name = "cffi" -version = "1.15.0" -description = "Foreign Function Interface for Python calling C code." -category = "main" -optional = true -python-versions = "*" - -[package.dependencies] -pycparser = "*" - [[package]] name = "cfgv" version = "3.3.1" @@ -178,7 +121,7 @@ python-versions = ">=3.6.1" [[package]] name = "charset-normalizer" -version = "2.0.8" +version = "2.0.9" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." category = "main" optional = false @@ -202,7 +145,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""} name = "colorama" version = "0.4.4" description = "Cross-platform colored terminal text." -category = "main" +category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" @@ -236,38 +179,6 @@ tomli = {version = "*", optional = true, markers = "extra == \"toml\""} [package.extras] toml = ["tomli"] -[[package]] -name = "cycler" -version = "0.11.0" -description = "Composable style cycles" -category = "main" -optional = true -python-versions = ">=3.6" - -[[package]] -name = "debugpy" -version = "1.5.1" -description = "An implementation of the Debug Adapter Protocol for Python" -category = "main" -optional = true -python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*" - -[[package]] -name = "decorator" -version = "5.1.0" -description = "Decorators for Humans" -category = "main" -optional = true -python-versions = ">=3.5" - -[[package]] -name = "defusedxml" -version = "0.7.1" -description = "XML bomb protection for Python stdlib modules" -category = "main" -optional = true -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" - [[package]] name = "distlib" version = "0.3.3" @@ -276,14 +187,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "entrypoints" -version = "0.3" -description = "Discover and load entry points from installed packages." -category = "main" -optional = true -python-versions = ">=2.7" - [[package]] name = "filelock" version = "3.4.0" @@ -437,27 +340,6 @@ python-versions = ">=3.6" [package.dependencies] flake8 = ">=3.8.0,<5" -[[package]] -name = "fonttools" -version = "4.28.2" -description = "Tools to manipulate font files" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.extras] -all = ["fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "zopfli (>=0.1.4)", "lz4 (>=1.7.4.2)", "matplotlib", "sympy", "skia-pathops (>=0.5.0)", "brotlicffi (>=0.8.0)", "scipy", "brotli (>=1.0.1)", "munkres", "unicodedata2 (>=13.0.0)", "xattr"] -graphite = ["lz4 (>=1.7.4.2)"] -interpolatable = ["scipy", "munkres"] -lxml = ["lxml (>=4.0,<5)"] -pathops = ["skia-pathops (>=0.5.0)"] -plot = ["matplotlib"] -symfont = ["sympy"] -type1 = ["xattr"] -ufo = ["fs (>=2.2.0,<3)"] -unicode = ["unicodedata2 (>=13.0.0)"] -woff = ["zopfli (>=0.1.4)", "brotlicffi (>=0.8.0)", "brotli (>=1.0.1)"] - [[package]] name = "frozenlist" version = "1.2.0" @@ -507,21 +389,6 @@ category = "main" optional = false python-versions = ">=3.5" -[[package]] -name = "importlib-resources" -version = "5.4.0" -description = "Read resources from Python packages" -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""} - -[package.extras] -docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] -testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-black (>=0.3.7)", "pytest-mypy"] - [[package]] name = "iniconfig" version = "1.1.1" @@ -530,226 +397,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "ipykernel" -version = "6.5.1" -description = "IPython Kernel for Jupyter" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "platform_system == \"Darwin\""} -debugpy = ">=1.0.0,<2.0" -ipython = ">=7.23.1" -jupyter-client = "<8.0" -matplotlib-inline = ">=0.1.0,<0.2.0" -tornado = ">=4.2,<7.0" -traitlets = ">=5.1.0,<6.0" - -[package.extras] -test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "nose", "ipyparallel"] - -[[package]] -name = "ipython" -version = "7.30.0" -description = "IPython: Productive Interactive Computing" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -appnope = {version = "*", markers = "sys_platform == \"darwin\""} -backcall = "*" -colorama = {version = "*", markers = "sys_platform == \"win32\""} -decorator = "*" -jedi = ">=0.16" -matplotlib-inline = "*" -pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} -pickleshare = "*" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" -pygments = "*" -traitlets = ">=4.2" - -[package.extras] -all = ["Sphinx (>=1.3)", "ipykernel", "ipyparallel", "ipywidgets", "nbconvert", "nbformat", "nose (>=0.10.1)", "notebook", "numpy (>=1.17)", "pygments", "qtconsole", "requests", "testpath"] -doc = ["Sphinx (>=1.3)"] -kernel = ["ipykernel"] -nbconvert = ["nbconvert"] -nbformat = ["nbformat"] -notebook = ["notebook", "ipywidgets"] -parallel = ["ipyparallel"] -qtconsole = ["qtconsole"] -test = ["nose (>=0.10.1)", "requests", "testpath", "pygments", "nbformat", "ipykernel", "numpy (>=1.17)"] - -[[package]] -name = "ipython-genutils" -version = "0.2.0" -description = "Vestigial utilities from IPython" -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "ipywidgets" -version = "7.6.5" -description = "IPython HTML widgets for Jupyter" -category = "main" -optional = true -python-versions = "*" - -[package.dependencies] -ipykernel = ">=4.5.1" -ipython = {version = ">=4.0.0", markers = "python_version >= \"3.3\""} -ipython-genutils = ">=0.2.0,<0.3.0" -jupyterlab-widgets = {version = ">=1.0.0", markers = "python_version >= \"3.6\""} -nbformat = ">=4.2.0" -traitlets = ">=4.3.1" -widgetsnbextension = ">=3.5.0,<3.6.0" - -[package.extras] -test = ["pytest (>=3.6.0)", "pytest-cov", "mock"] - -[[package]] -name = "jedi" -version = "0.18.1" -description = "An autocompletion tool for Python that can be used for text editors." -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -parso = ">=0.8.0,<0.9.0" - -[package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<7.0.0)"] - -[[package]] -name = "jinja2" -version = "3.0.3" -description = "A very fast and expressive template engine." -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -MarkupSafe = ">=2.0" - -[package.extras] -i18n = ["Babel (>=2.7)"] - -[[package]] -name = "jsonschema" -version = "4.2.1" -description = "An implementation of JSON Schema validation for Python" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -attrs = ">=17.4.0" -importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""} -pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2" - -[package.extras] -format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] -format_nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] - -[[package]] -name = "jupyter" -version = "1.0.0" -description = "Jupyter metapackage. Install all the Jupyter components in one go." -category = "main" -optional = true -python-versions = "*" - -[package.dependencies] -ipykernel = "*" -ipywidgets = "*" -jupyter-console = "*" -nbconvert = "*" -notebook = "*" -qtconsole = "*" - -[[package]] -name = "jupyter-client" -version = "7.1.0" -description = "Jupyter protocol implementation and client libraries" -category = "main" -optional = true -python-versions = ">=3.6.1" - -[package.dependencies] -entrypoints = "*" -jupyter-core = ">=4.6.0" -nest-asyncio = ">=1.5" -python-dateutil = ">=2.1" -pyzmq = ">=13" -tornado = ">=4.1" -traitlets = "*" - -[package.extras] -doc = ["myst-parser", "sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"] -test = ["codecov", "coverage", "ipykernel", "ipython", "mock", "mypy", "pre-commit", "pytest", "pytest-asyncio", "pytest-cov", "pytest-timeout", "jedi (<0.18)"] - -[[package]] -name = "jupyter-console" -version = "6.4.0" -description = "Jupyter terminal console" -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -ipykernel = "*" -ipython = "*" -jupyter-client = "*" -prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" -pygments = "*" - -[package.extras] -test = ["pexpect"] - -[[package]] -name = "jupyter-core" -version = "4.9.1" -description = "Jupyter core package. A base package on which Jupyter projects rely." -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""} -traitlets = "*" - -[[package]] -name = "jupyterlab-pygments" -version = "0.1.2" -description = "Pygments theme using JupyterLab CSS variables" -category = "main" -optional = true -python-versions = "*" - -[package.dependencies] -pygments = ">=2.4.1,<3" - -[[package]] -name = "jupyterlab-widgets" -version = "1.0.2" -description = "A JupyterLab extension." -category = "main" -optional = true -python-versions = ">=3.6" - -[[package]] -name = "kiwisolver" -version = "1.3.2" -description = "A fast implementation of the Cassowary constraint solver" -category = "main" -optional = true -python-versions = ">=3.7" - [[package]] name = "korean-lunar-calendar" version = "0.2.1" @@ -758,44 +405,6 @@ category = "main" optional = false python-versions = "*" -[[package]] -name = "markupsafe" -version = "2.0.1" -description = "Safely add untrusted strings to HTML/XML markup." -category = "main" -optional = true -python-versions = ">=3.6" - -[[package]] -name = "matplotlib" -version = "3.5.0" -description = "Python plotting package" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -cycler = ">=0.10" -fonttools = ">=4.22.0" -kiwisolver = ">=1.0.1" -numpy = ">=1.17" -packaging = ">=20.0" -pillow = ">=6.2.0" -pyparsing = ">=2.2.1" -python-dateutil = ">=2.7" -setuptools_scm = ">=4" - -[[package]] -name = "matplotlib-inline" -version = "0.1.3" -description = "Inline Matplotlib backend for Jupyter" -category = "main" -optional = true -python-versions = ">=3.5" - -[package.dependencies] -traitlets = "*" - [[package]] name = "mccabe" version = "0.6.1" @@ -804,14 +413,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "mistune" -version = "0.8.4" -description = "The fastest markdown parser in pure Python" -category = "main" -optional = true -python-versions = "*" - [[package]] name = "multidict" version = "5.2.0" @@ -845,81 +446,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "nbclient" -version = "0.5.9" -description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." -category = "main" -optional = true -python-versions = ">=3.6.1" - -[package.dependencies] -jupyter-client = ">=6.1.5" -nbformat = ">=5.0" -nest-asyncio = "*" -traitlets = ">=4.2" - -[package.extras] -dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] -sphinx = ["Sphinx (>=1.7)", "sphinx-book-theme", "mock", "moto", "myst-parser"] -test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] - -[[package]] -name = "nbconvert" -version = "6.3.0" -description = "Converting Jupyter Notebooks" -category = "main" -optional = true -python-versions = ">=3.7" - -[package.dependencies] -bleach = "*" -defusedxml = "*" -entrypoints = ">=0.2.2" -jinja2 = ">=2.4" -jupyter-core = "*" -jupyterlab-pygments = "*" -mistune = ">=0.8.1,<2" -nbclient = ">=0.5.0,<0.6.0" -nbformat = ">=4.4" -pandocfilters = ">=1.4.1" -pygments = ">=2.4.1" -testpath = "*" -traitlets = ">=5.0" - -[package.extras] -all = ["pytest", "pytest-cov", "pytest-dependency", "ipykernel", "ipywidgets (>=7)", "pyppeteer (==0.2.6)", "tornado (>=4.0)", "sphinx (>=1.5.1)", "sphinx-rtd-theme", "nbsphinx (>=0.2.12)", "ipython"] -docs = ["sphinx (>=1.5.1)", "sphinx-rtd-theme", "nbsphinx (>=0.2.12)", "ipython"] -serve = ["tornado (>=4.0)"] -test = ["pytest", "pytest-cov", "pytest-dependency", "ipykernel", "ipywidgets (>=7)", "pyppeteer (==0.2.6)"] -webpdf = ["pyppeteer (==0.2.6)"] - -[[package]] -name = "nbformat" -version = "5.1.3" -description = "The Jupyter Notebook format" -category = "main" -optional = true -python-versions = ">=3.5" - -[package.dependencies] -ipython-genutils = "*" -jsonschema = ">=2.4,<2.5.0 || >2.5.0" -jupyter-core = "*" -traitlets = ">=4.1" - -[package.extras] -fast = ["fastjsonschema"] -test = ["check-manifest", "fastjsonschema", "testpath", "pytest", "pytest-cov"] - -[[package]] -name = "nest-asyncio" -version = "1.5.1" -description = "Patch asyncio to allow nested event loops" -category = "main" -optional = true -python-versions = ">=3.5" - [[package]] name = "nodeenv" version = "1.6.0" @@ -928,96 +454,17 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "notebook" -version = "6.4.6" -description = "A web-based notebook environment for interactive computing" -category = "main" -optional = true -python-versions = ">=3.6" - -[package.dependencies] -argon2-cffi = "*" -ipykernel = "*" -ipython-genutils = "*" -jinja2 = "*" -jupyter-client = ">=5.3.4" -jupyter-core = ">=4.6.1" -nbconvert = "*" -nbformat = "*" -nest-asyncio = ">=1.5" -prometheus-client = "*" -pyzmq = ">=17" -Send2Trash = ">=1.8.0" -terminado = ">=0.8.3" -tornado = ">=6.1" -traitlets = ">=4.2.1" - -[package.extras] -docs = ["sphinx", "nbsphinx", "sphinxcontrib-github-alt", "sphinx-rtd-theme", "myst-parser"] -json-logging = ["json-logging"] -test = ["pytest", "coverage", "requests", "nbval", "selenium", "pytest-cov", "requests-unixsocket"] - 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-[package.dependencies] -ptyprocess = ">=0.5" - -[[package]] -name = "pickleshare" -version = "0.7.5" -description = "Tiny 'shelve'-like database with concurrency support" -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "pillow" -version = "8.4.0" -description = "Python Imaging Library (Fork)" -category = "main" -optional = true -python-versions = ">=3.6" - [[package]] name = "platformdirs" version = "2.4.0" @@ -1105,41 +525,11 @@ pyyaml = ">=5.1" toml = "*" virtualenv = ">=20.0.8" -[[package]] -name = "prometheus-client" -version = "0.12.0" -description = "Python client for the Prometheus monitoring system." -category = "main" -optional = true -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - -[package.extras] -twisted = ["twisted"] - -[[package]] -name = "prompt-toolkit" -version = "3.0.23" -description = "Library for building powerful interactive command lines in Python" -category = "main" -optional = true -python-versions = ">=3.6.2" - -[package.dependencies] -wcwidth = "*" - -[[package]] -name = "ptyprocess" -version = "0.7.0" -description = "Run a subprocess in a pseudo terminal" -category = "main" -optional = true -python-versions = "*" - [[package]] name = "py" version = "1.11.0" description = "library with cross-python path, ini-parsing, io, code, log facilities" -category = "main" +category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" @@ -1151,14 +541,6 @@ category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" -[[package]] -name = "pycparser" -version = "2.21" -description = "C parser in Python" -category = "main" -optional = true -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - [[package]] name = "pyflakes" version = "2.4.0" @@ -1167,14 +549,6 @@ category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" -[[package]] -name = "pygments" -version = "2.10.0" -description = "Pygments is a syntax highlighting package written in Python." -category = "main" -optional = true -python-versions = ">=3.5" - [[package]] name = "pymeeus" version = "0.5.11" @@ -1187,21 +561,13 @@ python-versions = "*" name = "pyparsing" version = "3.0.6" description = "Python parsing module" -category = "main" +category = "dev" optional = false python-versions = ">=3.6" [package.extras] diagrams = ["jinja2", "railroad-diagrams"] -[[package]] -name = "pyrsistent" -version = "0.18.0" -description = "Persistent/Functional/Immutable data structures" -category = "main" -optional = true -python-versions = ">=3.6" - [[package]] name = "pytest" version = "6.2.5" @@ -1295,22 +661,6 @@ category = "main" optional = false python-versions = "*" -[[package]] -name = "pywin32" -version = "302" -description = "Python for Window Extensions" -category = "main" -optional = true -python-versions = "*" - -[[package]] -name = "pywinpty" -version = "1.1.6" -description = "Pseudo terminal support for Windows from Python." -category = "main" -optional = true -python-versions = ">=3.6" - [[package]] name = "pyyaml" version = "6.0" @@ -1319,84 +669,6 @@ category = "dev" optional = false python-versions = ">=3.6" -[[package]] -name = "pyzmq" -version = "22.3.0" -description = "Python bindings for 0MQ" -category = "main" -optional = true -python-versions = ">=3.6" - 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