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FR_O.py
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FR_O.py
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from datetime import datetime, timedelta
from logging import getLogger
from requests import Response, Session
from electricitymap.contrib.lib.models.event_lists import (
PriceList,
ProductionBreakdownList,
)
from electricitymap.contrib.lib.models.events import (
EventSourceType,
ProductionMix,
StorageMix,
)
from electricitymap.contrib.lib.types import ZoneKey
from .lib.config import refetch_frequency
from .lib.exceptions import ParserException
DOMAIN_MAPPING = {
"FR-COR": "https://opendata-corse.edf.fr",
"RE": "https://opendata-reunion.edf.fr",
"GF": "https://opendata-guyane.edf.fr",
"MQ": "https://opendata-martinique.edf.fr",
"GP": "https://opendata-guadeloupe.edf.fr",
}
LIVE_DATASETS = {
"FR-COR": "production-delectricite-par-filiere-en-temps-reel",
"GP": "mix-temps-reel-guadeloupe",
"RE": "prod-electricite-temps-reel",
"GF": "production-d-electricite-par-filiere-en-temps-reel",
"MQ": "production-delectricite-par-filiere-en-temps-reel",
}
HISTORICAL_MAPPING = {
"FR-COR": "Corse",
"RE": "Réunion",
"GF": "Guyane",
"MQ": "Martinique",
"GP": "Guadeloupe",
}
API_PARAMETER_GROUPS = {
"production": {
"biomass": [
"biomasse",
"biomasse_mw",
"biomasse_mwh",
"bioenergies",
"bioenergies_mw",
"bioenergies_mwh",
],
"coal": [
"charbon",
],
"gas": [
"thermique_mw",
"thermique_mwh",
"turbines_a_combustion",
],
"geothermal": [
"geothermie",
"geothermie_mw",
],
"hydro": [
"hydraulique",
"hydraulique_mw",
"hydraulique_mwh",
"micro_hydro",
"micro_hydraulique_mw",
],
"oil": ["diesel", "moteur_diesel", "centrale_au_fioul", "moteurs_diesels"],
"solar": [
"photovoltaique",
"photovoltaique0",
"photovoltaique_mw",
"photovoltaique_mwh",
"solaire_mw",
],
"wind": [
"eolien",
"eolien_mw",
"eolien_mwh",
],
"unknown": ["bagasse_charbon_mwh", "charbon_bagasse_mw"],
},
"storage": {"battery": ["solde_stockage", "stockage"]},
"price": {
"price": ["cout_moyen_de_production_eur_mwh"],
},
}
PRODUCTION_MAPPING = {
API_TYPE: data_type
for key in ["production"]
for data_type, groups in API_PARAMETER_GROUPS[key].items()
for API_TYPE in groups
}
STORAGE_MAPPING = {
API_TYPE: data_type
for key in ["storage"]
for data_type, groups in API_PARAMETER_GROUPS[key].items()
for API_TYPE in groups
}
PRICE_MAPPING = {
API_TYPE: data_type
for key in ["price"]
for data_type, groups in API_PARAMETER_GROUPS[key].items()
for API_TYPE in groups
}
IGNORED_VALUES = ["jour", "total", "statut", "date", "heure", "liaisons", "tac"]
def generate_url(zone_key, target_datetime):
if target_datetime:
return "https://opendata.edf.fr/api/explore/v2.1/catalog/datasets/courbe-de-charge-de-la-production-delectricite-par-filiere/exports/json"
return f"{DOMAIN_MAPPING[zone_key]}/api/v2/catalog/datasets/{LIVE_DATASETS[zone_key]}/exports/json"
def fetch_data(
zone_key: ZoneKey,
session: Session | None = None,
target_datetime: datetime | None = None,
) -> tuple[list, str, str]:
ses = session or Session()
if target_datetime is None and zone_key not in LIVE_DATASETS:
raise ParserException(
"FR_O.py",
f"Live data not implemented for {zone_key} in this parser.",
zone_key,
)
target_date = target_datetime.strftime("%Y-%m-%d") if target_datetime else None
past_date = (
(target_datetime - timedelta(days=3)).strftime("%Y-%m-%d")
if target_datetime
else None
)
URL_QUERIES: dict[str, str | None] = (
{
"timezone": "UTC",
"order_by": "date_heure",
"where": f"date_heure >= date'{past_date}' AND date_heure <= date'{target_date}'",
"refine": f"territoire:{HISTORICAL_MAPPING[zone_key]}",
}
if target_datetime
else {
"timezone": "UTC",
"order_by": "date",
}
)
url = generate_url(zone_key, target_datetime)
response: Response = ses.get(url, params=URL_QUERIES)
data: dict | list | None = response.json()
if data == []:
raise ParserException(
"FR_O.py",
f"No data available for {zone_key} for {target_datetime.strftime('%Y')}"
if target_datetime
else f"No live data available for {zone_key}.",
zone_key,
)
elif isinstance(data, dict):
if data.get("errorcode") == "10002":
raise ParserException(
"FR_O.py",
f"Rate limit exceeded. Please try again later after: {data.get('reset_time')}",
)
elif data.get("error_code") == "ODSQLError":
raise ParserException(
"FR_O.py",
"Query malformed. Please check the parameters. If this was previously working there has likely been a change in the API.",
)
if not isinstance(data, list):
raise ParserException(
"FR_O.py",
f"Unexpected data format for {zone_key} for {target_datetime}"
if target_datetime
else f"Unexpected data format for {zone_key}.",
zone_key,
)
source = url.split("//")[1].split("/")[0]
return data, "date_heure" if target_datetime else "date", source
@refetch_frequency(timedelta(hours=72))
def fetch_production(
zone_key: ZoneKey,
session: Session | None = None,
target_datetime: datetime | None = None,
logger=getLogger(__name__),
):
production_objects, date_string, source = fetch_data(
zone_key, session, target_datetime
)
production_breakdown_list = ProductionBreakdownList(logger=logger)
for production_object in production_objects:
production = ProductionMix()
storage = StorageMix()
for mode_key in production_object:
if mode_key in PRODUCTION_MAPPING:
production.add_value(
PRODUCTION_MAPPING[mode_key],
production_object[mode_key],
correct_negative_with_zero=True,
)
elif mode_key in STORAGE_MAPPING:
storage.add_value(
STORAGE_MAPPING[mode_key], -production_object[mode_key]
)
elif mode_key in IGNORED_VALUES:
pass
else:
logger.warning(
f"Unknown mode_key: '{mode_key}' encountered for {zone_key}."
)
production_breakdown_list.append(
zoneKey=zone_key,
datetime=datetime.fromisoformat(production_object[date_string]),
production=production,
storage=storage,
source=source,
sourceType=EventSourceType.estimated
if production_object.get("statut") == "Estimé"
else EventSourceType.measured,
)
return production_breakdown_list.to_list()
@refetch_frequency(timedelta(hours=72))
def fetch_price(
zone_key: ZoneKey,
session: Session | None = None,
target_datetime: datetime | None = None,
logger=getLogger(__name__),
):
data_objects, date_string, source = fetch_data(zone_key, session, target_datetime)
price_list = PriceList(logger=logger)
for data_object in data_objects:
price: float | int | None = None
for mode_key in data_object:
if mode_key in PRICE_MAPPING:
price = data_object[mode_key]
break
if price is not None:
price_list.append(
zoneKey=zone_key,
currency="EUR",
datetime=datetime.fromisoformat(data_object[date_string]),
source=source,
price=price,
)
return price_list.to_list()