def power_flows_week(
time_series: TimeSeries,
network_region_code: str,
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
query = interconnector_power_flow(time_series=time_series,
network_region=network_region_code)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
raise Exception("No results from query: {}".format(query))
imports = [
DataQueryResult(interval=i[0],
result=i[2],
group_by="imports" if len(i) > 1 else None)
for i in row
]
exports = [
DataQueryResult(interval=i[0],
result=i[3],
group_by="exports" if len(i) > 1 else None)
for i in row
]
result = stats_factory(
imports,
# code=network_region_code or network.code,
network=time_series.network,
period=human_to_period("7d"),
interval=human_to_interval("5m"),
units=get_unit("power"),
region=network_region_code,
fueltech_group=True,
)
if not result:
raise Exception("No results")
result_exports = stats_factory(
exports,
# code=network_region_code or network.code,
network=time_series.network,
period=human_to_period("7d"),
interval=human_to_interval("5m"),
units=get_unit("power"),
region=network_region_code,
fueltech_group=True,
)
result.append_set(result_exports)
return result
def power_network_region_fueltech(
network_code: str = Query(..., description="Network code"),
network_region_code: str = Query(..., description="Network region code"),
month: date = Query(datetime.now().date(), description="Month to query"),
) -> OpennemDataSet:
network = network_from_network_code(network_code)
interval_obj = network.get_interval()
period_obj = human_to_period("1M")
scada_range = get_scada_range(network=network)
if not scada_range:
raise Exception("Require a scada range")
if not network:
raise Exception("Network not found")
time_series = TimeSeries(
start=scada_range.start,
month=month,
network=network,
interval=interval_obj,
period=period_obj,
)
stat_set = power_week(time_series,
network_region_code,
include_capacities=True)
if not stat_set:
raise Exception("No results")
return stat_set
def gov_stats_cpi() -> Optional[OpennemDataSet]:
engine = get_database_engine()
query = country_stats_query(StatTypes.CPI)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in row
]
if len(stats) < 1:
logger.error("No results for gov_stats_cpi returing blank set")
return None
result = stats_factory(
stats,
code="au.cpi",
network=NetworkNEM,
interval=human_to_interval("1Q"),
period=human_to_period("all"),
units=get_unit("cpi"),
group_field="gov",
)
return result
def export_flows() -> None:
date_range = get_scada_range(network=NetworkNEM)
interchange_stat = StatExport(
stat_type=StatType.power,
priority=PriorityType.live,
country="au",
date_range=date_range,
network=NetworkNEM,
interval=NetworkNEM.get_interval(),
period=human_to_period("7d"),
)
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
network=interchange_stat.network,
interval=interchange_stat.interval,
period=interchange_stat.period,
)
stat_set = power_flows_network_week(time_series=time_series)
if stat_set:
write_output(
f"v3/stats/au/{interchange_stat.network.code}/flows/7d.json",
stat_set)
def power_unit(
unit_code: str = Query(..., description="Unit code"),
network_code: str = Query(..., description="Network code"),
interval_human: str = Query(None, description="Interval"),
period_human: str = Query("7d", description="Period"),
engine=Depends(get_database_engine),
) -> OpennemDataSet:
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval_human:
interval_human = "{}m".format(network.interval_size)
interval = human_to_interval(interval_human)
period = human_to_period(period_human)
units = get_unit("power")
stats = []
facility_codes = [normalize_duid(unit_code)]
query = power_facility_query(facility_codes, network.code, interval=interval, period=period)
with engine.connect() as c:
results = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in results
]
if len(stats) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Unit stats not found",
)
output = stats_factory(
stats,
code=unit_code,
interval=interval,
period=period,
units=units,
network=network,
)
if not output:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No stats found",
)
return output
def energy_network_api(
engine=Depends(get_database_engine),
network_code: str = Query(..., description="Network code"),
interval_human: str = Query("1d", description="Interval"),
period_human: str = Query("1Y", description="Period"),
) -> OpennemDataSet:
results = []
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval_human:
interval_human = "{}m".format(network.interval_size)
interval = human_to_interval(interval_human)
period = human_to_period(period_human)
units = get_unit("energy_giga")
query = energy_network(network=network, interval=interval, period=period)
with engine.connect() as c:
results = list(c.execute(query))
if len(results) < 1:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="No results")
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in results
]
result = stats_factory(
stats,
code=network.code,
network=network,
interval=interval,
period=period,
units=units,
)
if not result:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results found",
)
return result
def get_date_range(network: NetworkSchema) -> DatetimeRange:
date_range = get_scada_range(network=NetworkNEM)
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
interval=human_to_interval("1d"),
period=human_to_period("all"),
network=network,
)
return time_series.get_range()
def power_network_region_fueltech(
network_code: str = Query(..., description="Network code"),
network_region_code: str = Query(..., description="Network region code"),
month: date = Query(datetime.now().date(), description="Month to query"),
) -> OpennemDataSet:
network = None
try:
network = network_from_network_code(network_code)
except Exception:
raise HTTPException(detail="Network not found", status_code=status.HTTP_404_NOT_FOUND)
interval_obj = network.get_interval()
period_obj = human_to_period("1M")
scada_range = get_scada_range(network=network)
if not scada_range:
raise Exception("Require a scada range")
if not network:
raise Exception("Network not found")
networks = [network]
if network == NetworkNEM:
networks.append(NetworkAEMORooftop)
networks.append(NetworkAEMORooftopBackfill)
elif network == NetworkWEM:
networks.append(NetworkAPVI)
time_series = TimeSeries(
start=scada_range.start,
month=month,
network=network,
networks=networks,
interval=interval_obj,
period=period_obj,
)
stat_set = power_week(
time_series, network_region_code, include_capacities=True, networks_query=networks
)
if not stat_set:
raise Exception("No results")
return stat_set
def demand_week(
time_series: TimeSeries,
network_region_code: Optional[str],
networks_query: Optional[List[NetworkSchema]] = None,
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
query = network_demand_query(
time_series=time_series,
network_region=network_region_code,
networks_query=networks_query,
)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
logger.error(
"No results from network_demand_query with {}".format(time_series))
return None
demand = [
DataQueryResult(interval=i[0],
result=i[2],
group_by="demand" if len(i) > 1 else None) for i in row
]
result = stats_factory(
demand,
# code=network_region_code or network.code,
network=time_series.network,
period=human_to_period("7d"),
interval=human_to_interval("5m"),
units=get_unit("demand"),
region=network_region_code,
)
if not result:
logger.error(
"No results from network_demand_query with {}".format(time_series))
return None
return result
def get_power_example() -> OpennemDataSet:
network = network_from_network_code("NEM")
interval = human_to_interval("5m")
units = get_unit("power")
period = human_to_period("7d")
network_region_code = "NSW1"
test_rows = []
dt = datetime.fromisoformat("2021-01-15 10:00:00")
for ft in ["coal_black", "coal_brown"]:
for v in range(0, 3):
test_rows.append([dt, ft, v])
dt = dt + timedelta(minutes=5)
stats = [
DataQueryResult(interval=i[0],
result=i[2],
group_by=i[1] if len(i) > 1 else None)
for i in test_rows
]
assert len(stats) == 6, "Should have 6 stats"
result = stats_factory(
stats,
code=network_region_code or network.code,
network=network,
interval=interval,
period=period,
units=units,
region=network_region_code,
fueltech_group=True,
)
if not result:
raise Exception("Bad unit test data")
with open("power-nsw1.json", "w") as fh:
fh.write(result.json(indent=4))
return result
def export_all_monthly() -> None:
session = get_scoped_session()
all_monthly = OpennemDataSet(code="au",
data=[],
version=get_version(),
created_at=datetime.now())
cpi = gov_stats_cpi()
all_monthly.append_set(cpi)
# Iterate networks and network regions
networks = [NetworkNEM, NetworkWEM]
for network in networks:
network_regions = session.query(NetworkRegion).filter(
NetworkRegion.network_id == network.code).all()
for network_region in network_regions:
networks = []
logging.info(
"Exporting monthly for network {} and region {}".format(
network.code, network_region.code))
if network_region.code == "WEM":
networks = [NetworkWEM, NetworkAPVI]
if network == NetworkNEM:
networks = [NetworkNEM, NetworkAEMORooftop]
logger.debug("Running monthlies for {} and {}".format(
network.code, network_region.code))
scada_range: ScadaDateRange = get_scada_range(network=network,
networks=networks,
energy=True)
if not scada_range or not scada_range.start:
logger.error(
"Could not get scada range for network {} and energy {}".
format(network, True))
continue
time_series = TimeSeries(
start=scada_range.start,
end=scada_range.end,
network=network,
interval=human_to_interval("1M"),
period=human_to_period("all"),
)
stat_set = energy_fueltech_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
if not stat_set:
continue
demand_energy_and_value = demand_network_region_daily(
time_series=time_series,
network_region_code=network_region.code,
networks=networks)
stat_set.append_set(demand_energy_and_value)
if network == NetworkNEM:
interconnector_flows = energy_interconnector_flows_and_emissions(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_flows)
all_monthly.append_set(stat_set)
bom_station = get_network_region_weather_station(
network_region.code)
if bom_station:
try:
weather_stats = weather_daily(
time_series=time_series,
station_code=bom_station,
network_region=network_region.code,
)
all_monthly.append_set(weather_stats)
except Exception:
pass
write_output("v3/stats/au/all/monthly.json", all_monthly)
def power_network_fueltech_api(
network_code: str = Query(..., description="Network code"),
network_region: str = Query(None, description="Network region"),
interval_human: str = Query(None, description="Interval"),
period_human: str = Query("7d", description="Period"),
engine=Depends(get_database_engine),
) -> OpennemDataSet:
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval_human:
interval_human = "{}m".format(network.interval_size)
interval = human_to_interval(interval_human)
period = human_to_period(period_human)
units = get_unit("power")
scada_range = get_scada_range(network=network)
query = power_network_fueltech(
network=network,
interval=interval,
period=period,
network_region=network_region,
scada_range=scada_range,
)
with engine.connect() as c:
results = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in results
]
if len(stats) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
result = stats_factory(
stats,
code=network.code,
network=network,
interval=interval,
period=period,
units=units,
region=network_region,
fueltech_group=True,
)
if not result:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results found",
)
return result
def energy_station(
engine=Depends(get_database_engine),
session: Session = Depends(get_database_session),
network_code: str = Query(..., description="Network code"),
station_code: str = Query(..., description="Station Code"),
interval: str = Query(None, description="Interval"),
period: str = Query("7d", description="Period"),
) -> OpennemDataSet:
"""
Get energy output for a station (list of facilities)
over a period
"""
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval:
# @NOTE rooftop data is 15m
if station_code.startswith("ROOFTOP"):
interval = "15m"
else:
interval = "{}m".format(network.interval_size)
interval_obj = human_to_interval(interval)
period_obj = human_to_period(period)
units = get_unit("energy")
station = (
session.query(Station)
.join(Station.facilities)
.filter(Station.code == station_code)
.filter(Facility.network_id == network.code)
.one_or_none()
)
if not station:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Station not found")
if len(station.facilities) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station has no facilities",
)
facility_codes = list(set([f.code for f in station.facilities]))
query = energy_facility_query(
facility_codes,
network=network,
interval=interval_obj,
period=period_obj,
)
logger.debug(query)
with engine.connect() as c:
row = list(c.execute(query))
if len(row) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
results_energy = [
DataQueryResult(interval=i[0], group_by=i[1], result=i[2] if len(i) > 1 else None)
for i in row
]
results_market_value = [
DataQueryResult(interval=i[0], group_by=i[1], result=i[3] if len(i) > 1 else None)
for i in row
]
results_emissions = [
DataQueryResult(interval=i[0], group_by=i[1], result=i[4] if len(i) > 1 else None)
for i in row
]
if len(results_energy) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
stats = stats_factory(
stats=results_energy,
units=units,
network=network,
interval=interval_obj,
period=period_obj,
code=station_code,
include_group_code=True,
)
if not stats:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
stats_market_value = stats_factory(
stats=results_market_value,
units=get_unit("market_value"),
network=network,
interval=interval_obj,
period=period_obj,
code=station_code,
include_group_code=True,
)
stats.append_set(stats_market_value)
stats_emissions = stats_factory(
stats=results_emissions,
units=get_unit("emissions"),
network=network,
interval=interval_obj,
period=period_obj,
code=network.code.lower(),
include_group_code=True,
)
stats.append_set(stats_emissions)
return stats
def energy_interconnector_emissions_region_daily(
time_series: TimeSeries,
network_region_code: str,
networks_query: Optional[List[NetworkSchema]] = None,
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
period: TimePeriod = human_to_period("1Y")
units = get_unit("emissions")
query = energy_network_interconnector_emissions_query(
time_series=time_series,
network_region=network_region_code,
networks_query=networks_query,
)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
return None
stats = [
RegionFlowEmissionsResult(
interval=i[0],
flow_from=i[1],
flow_to=i[2],
energy=i[3],
flow_from_emissions=i[4],
flow_to_emissions=i[5],
)
for i in row
]
stats_grouped = net_flows_emissions(network_region_code, stats, time_series.interval)
imports = stats_grouped["imports"]
exports = stats_grouped["exports"]
# imports = [DataQueryResult(interval=i[0], group_by="imports", result=i[5]) for i in row]
# exports = [DataQueryResult(interval=i[0], group_by="exports", result=i[4]) for i in row]
result = stats_factory(
imports,
network=time_series.network,
period=period,
interval=time_series.interval,
units=units,
region=network_region_code,
fueltech_group=True,
localize=False,
)
# Bail early on no interconnector
# don't error
if not result:
return result
result_exports = stats_factory(
exports,
network=time_series.network,
period=period,
interval=time_series.interval,
units=units,
region=network_region_code,
fueltech_group=True,
localize=False,
)
result.append_set(result_exports)
return result
def power_station(
station_code: str = Query(..., description="Station code"),
network_code: str = Query(..., description="Network code"),
since: datetime = Query(None, description="Since time"),
interval_human: str = Query(None, description="Interval"),
period_human: str = Query("7d", description="Period"),
session: Session = Depends(get_database_session),
engine=Depends(get_database_engine),
) -> OpennemDataSet:
if not since:
since = datetime.now() - human_to_timedelta("7d")
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval_human:
# @NOTE rooftop data is 15m
if station_code.startswith("ROOFTOP"):
interval_human = "15m"
else:
interval_human = "{}m".format(network.interval_size)
interval = human_to_interval(interval_human)
period = human_to_period(period_human)
units = get_unit("power")
station = (
session.query(Station)
.join(Facility)
.filter(Station.code == station_code)
.filter(Facility.network_id == network.code)
.filter(Station.approved.is_(True))
.one_or_none()
)
if not station:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Station not found")
facility_codes = list(set([f.code for f in station.facilities]))
stats = []
query = power_facility_query(facility_codes, network=network, interval=interval, period=period)
logger.debug(query)
with engine.connect() as c:
results = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in results
]
if len(stats) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
result = stats_factory(
stats,
code=station_code,
network=network,
interval=interval,
period=period,
include_group_code=True,
units=units,
)
if not result:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results found",
)
return result
def get_range(self) -> DatetimeRange:
"""Return a DatetimeRange from the time series for queries"""
start = self.start
end = self.end
# If its a forward looking forecast
# jump out early
if self.forecast:
start = self.end + timedelta(minutes=self.interval.interval)
end = self.end + get_human_interval(self.forecast_period)
start = start.astimezone(self.network.get_fixed_offset())
end = end.astimezone(self.network.get_fixed_offset())
return DatetimeRange(start=start, end=end, interval=self.interval)
# subtract the period (ie. 7d from the end for start if not all)
if self.period == human_to_period("all"):
start = date_trunc(start, self.interval.trunc)
start = start.replace(
hour=0, minute=0, second=0, tzinfo=self.network.get_fixed_offset()
)
# If its all per month take the end of the last month
if self.interval == human_to_interval("1M"):
end = date_trunc(get_end_of_last_month(end), "day")
end = end.replace(
hour=23, minute=59, second=59, tzinfo=self.network.get_fixed_offset()
)
self.year = None
else:
start = self.end - get_human_interval(self.period.period_human)
if self.year:
if self.year > end.year:
raise Exception("Specified year is great than end year")
start = start.replace(
year=self.year,
month=1,
day=1,
hour=0,
minute=0,
second=0,
tzinfo=self.network.get_fixed_offset(),
)
end = datetime(
year=self.year,
month=12,
day=31,
hour=23,
minute=59,
second=59,
tzinfo=self.network.get_fixed_offset(),
)
if self.year == CUR_YEAR:
today = datetime.now(tz=self.network.get_fixed_offset())
end = datetime(
year=CUR_YEAR, month=today.month, day=today.day, hour=23, minute=59, second=59
)
end = end - timedelta(days=1)
end = end.replace(tzinfo=self.network.get_fixed_offset())
if self.end.date() < today.date():
end = self.end
if self.month:
start = datetime(
year=self.month.year,
month=self.month.month,
day=1,
hour=0,
minute=0,
second=0,
tzinfo=self.network.get_fixed_offset(),
)
end = start + get_human_interval("1M") - timedelta(days=1)
end = end.replace(
hour=23,
minute=59,
second=59,
)
# localize times
if not start.tzinfo or start.tzinfo != self.network.get_fixed_offset():
start = start.astimezone(self.network.get_fixed_offset())
if not end.tzinfo or end.tzinfo != self.network.get_fixed_offset():
end = end.astimezone(self.network.get_fixed_offset())
dtr = DatetimeRange(start=start, end=end, interval=self.interval)
return dtr
def energy_interconnector_region_daily(
time_series: TimeSeries,
network_region_code: str,
networks_query: Optional[List[NetworkSchema]] = None,
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
period: TimePeriod = human_to_period("1Y")
units = get_unit("energy_giga")
query = energy_network_flow_query(
time_series=time_series,
network_region=network_region_code,
)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
return None
imports = [DataQueryResult(interval=i[0], group_by="imports", result=i[1]) for i in row]
exports = [DataQueryResult(interval=i[0], group_by="exports", result=i[2]) for i in row]
imports_mv = [DataQueryResult(interval=i[0], group_by="imports", result=i[3]) for i in row]
exports_mv = [DataQueryResult(interval=i[0], group_by="exports", result=i[4]) for i in row]
result = stats_factory(
imports,
network=time_series.network,
period=period,
interval=time_series.interval,
units=units,
region=network_region_code,
fueltech_group=True,
# localize=False,
)
# Bail early on no interconnector
# don't error
if not result:
logger.warn("No interconnector energy result")
return result
result_exports = stats_factory(
exports,
network=time_series.network,
period=period,
interval=time_series.interval,
units=units,
region=network_region_code,
fueltech_group=True,
)
result.append_set(result_exports)
result_imports_mv = stats_factory(
imports_mv,
units=get_unit("market_value"),
network=time_series.network,
fueltech_group=True,
interval=time_series.interval,
region=network_region_code,
period=time_series.period,
code=time_series.network.code.lower(),
localize=False,
)
result.append_set(result_imports_mv)
result_export_mv = stats_factory(
exports_mv,
units=get_unit("market_value"),
network=time_series.network,
fueltech_group=True,
interval=time_series.interval,
region=network_region_code,
period=time_series.period,
code=time_series.network.code.lower(),
localize=False,
)
result.append_set(result_export_mv)
return result
def emission_factor_per_network( # type: ignore
engine=Depends(get_database_engine), # type: ignore
network_code: str = Query(..., description="Network code"),
interval: str = Query("30m", description="Interval size"),
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
network = None
try:
network = network_from_network_code(network_code)
except Exception:
raise HTTPException(detail="Network not found", status_code=status.HTTP_404_NOT_FOUND)
interval_obj = human_to_interval(interval)
period_obj = human_to_period("7d")
if not interval_obj:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Invalid interval size")
scada_range = get_scada_range(network=network)
if not scada_range:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="Could not find a date range",
)
if not network:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="Network not found",
)
time_series = TimeSeries(
start=scada_range.start,
network=network,
interval=interval_obj,
period=period_obj,
)
query = emission_factor_region_query(time_series=time_series)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
emission_factors = [
DataQueryResult(interval=i[0], result=i[2], group_by=i[1] if len(i) > 1 else None)
for i in row
]
result = stats_factory(
emission_factors,
network=time_series.network,
period=time_series.period,
interval=time_series.interval,
units=get_unit("emissions_factor"),
group_field="emission_factor",
include_group_code=True,
include_code=True,
)
if not result or not result.data:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
return result
def fueltech_demand_mix(
engine=Depends(get_database_engine), # type: ignore
network_code: str = Query(..., description="Network code"),
) -> OpennemDataSet:
"""Return fueltech proportion of demand for a network
Args:
engine ([type], optional): Database engine. Defaults to Depends(get_database_engine).
Raises:
HTTPException: No results
Returns:
OpennemData: data set
"""
engine = get_database_engine()
network = None
try:
network = network_from_network_code(network_code)
except Exception:
raise HTTPException(detail="Network not found", status_code=status.HTTP_404_NOT_FOUND)
interval_obj = human_to_interval("5m")
period_obj = human_to_period("1d")
scada_range = get_scada_range(network=network)
if not scada_range:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="Could not find a date range",
)
if not network:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="Network not found",
)
time_series = TimeSeries(
start=scada_range.start,
network=network,
interval=interval_obj,
period=period_obj,
)
query = network_fueltech_demand_query(time_series=time_series)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
result_set = [
DataQueryResult(interval=i[0], result=i[2], group_by=i[1] if len(i) > 1 else None)
for i in row
]
result = stats_factory(
result_set,
network=time_series.network,
period=time_series.period,
interval=time_series.interval,
units=get_unit("emissions_factor"),
group_field="emission_factor",
include_group_code=True,
include_code=True,
)
if not result or not result.data:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
return result
def export_electricitymap() -> None:
date_range = get_scada_range(network=NetworkNEM)
if not date_range.start:
raise Exception("Could not get a scada range in EM export")
interchange_stat = StatExport(
stat_type=StatType.power,
priority=PriorityType.live,
country="au",
date_range=date_range,
network=NetworkNEM,
interval=NetworkNEM.get_interval(),
period=human_to_period("1d"),
)
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
network=interchange_stat.network,
networks=[NetworkNEM, NetworkAEMORooftop, NetworkAEMORooftopBackfill],
interval=interchange_stat.interval,
period=interchange_stat.period,
)
stat_set = power_flows_network_week(time_series=time_series)
if not stat_set:
raise Exception("No flow results for electricitymap export")
em_set = OpennemDataSet(type="custom",
version=get_version(),
created_at=datetime.now(),
data=[])
INVERT_SETS = ["VIC1->NSW1", "VIC1->SA1"]
for ds in stat_set.data:
if ds.code in INVERT_SETS:
ds_inverted = invert_flow_set(ds)
em_set.data.append(ds_inverted)
logging.info("Inverted {}".format(ds.code))
else:
em_set.data.append(ds)
for region in ["NSW1", "QLD1", "VIC1", "TAS1", "SA1"]:
power_set = power_week(
time_series,
region,
include_capacities=True,
include_code=False,
networks_query=[
NetworkNEM, NetworkAEMORooftop, NetworkAEMORooftopBackfill
],
)
if power_set:
em_set.append_set(power_set)
date_range = get_scada_range(network=NetworkWEM)
# WEM custom
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
network=NetworkWEM,
networks=[NetworkWEM, NetworkAPVI],
interval=NetworkWEM.get_interval(),
period=interchange_stat.period,
)
power_set = power_week(
time_series,
"WEM",
include_capacities=True,
networks_query=[NetworkWEM, NetworkAPVI],
include_code=False,
)
if power_set:
em_set.append_set(power_set)
write_output("v3/clients/em/latest.json", em_set)
def power_flows_network_week(
engine=Depends(get_database_engine), # type: ignore
network_code: str = Query(..., description="Network code"),
month: date = Query(datetime.now().date(), description="Month to query"),
) -> Optional[OpennemDataSet]:
engine = get_database_engine()
network = network_from_network_code(network_code)
interval_obj = network.get_interval()
period_obj = human_to_period("1M")
scada_range = get_scada_range(network=network)
if not scada_range:
raise Exception("Require a scada range")
if not network:
raise Exception("Network not found")
time_series = TimeSeries(
start=scada_range.start,
month=month,
network=network,
interval=interval_obj,
period=period_obj,
)
query = interconnector_flow_network_regions_query(time_series=time_series)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
raise Exception("No results from query: {}".format(query))
imports = [
DataQueryResult(interval=i[0], result=i[4], group_by=i[1] if len(i) > 1 else None)
for i in row
]
result = stats_factory(
imports,
# code=network_region_code or network.code,
network=time_series.network,
period=time_series.period,
interval=time_series.interval,
units=get_unit("regional_trade"),
# fueltech_group=True,
group_field="power",
include_group_code=True,
include_code=True,
)
if not result or not result.data:
raise Exception("No results")
INVERT_SETS = ["VIC1->NSW1", "VIC1->SA1"]
inverted_data = []
for ds in result.data:
if ds.code in INVERT_SETS:
ds_inverted = invert_flow_set(ds)
inverted_data.append(ds_inverted)
else:
inverted_data.append(ds)
result.data = inverted_data
return result
def price_network_region_api(
engine=Depends(get_database_engine),
network_code: str = Query(..., description="Network code"),
network_region_code: str = Query(..., description="Region code"),
interval_human: str = Query(None, description="Interval"),
period_human: str = Query("7d", description="Period"),
year: Optional[int] = None,
) -> OpennemDataSet:
network = network_from_network_code(network_code)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No such network",
)
if not interval_human:
interval_human = "{}m".format(network.interval_size)
interval = human_to_interval(interval_human)
period_obj = None
if period_human:
period_obj = human_to_period(period_human)
units = get_unit("price")
scada_range = get_scada_range(network=network)
if period_obj and period_obj.period_human == "all" and interval.interval_human == "1M":
query = price_network_monthly(
network=network,
network_region_code=network_region_code,
scada_range=scada_range,
)
else:
query = price_network_region(
network=network,
network_region_code=network_region_code,
interval=interval,
period=period_obj,
scada_range=scada_range,
year=year,
)
with engine.connect() as c:
results = list(c.execute(query))
if len(results) < 1:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="No data found")
stats = [
DataQueryResult(interval=i[0], result=i[2], group_by=i[1] if len(i) > 1 else None)
for i in results
]
result = stats_factory(
stats,
code=network.code,
region=network_region_code,
network=network,
interval=interval,
period=period_obj,
units=units,
group_field="price",
)
if not result:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results found",
)
return result
def station_observations_api(
station_code: str = Query(None, description="Station code"),
interval_human: str = Query("15m", description="Interval"),
period_human: str = Query("7d", description="Period"),
station_codes: List[str] = [],
timezone: str = None,
offset: str = None,
year: int = None,
engine=Depends(get_database_engine),
) -> OpennemDataSet:
units = get_unit("temperature")
if not interval_human:
interval_human = "15m"
if not period_human:
period_human = "7d"
if station_code:
station_codes = [station_code]
interval = human_to_interval(interval_human)
period = human_to_period(period_human)
if timezone:
timezone = ZoneInfo(timezone)
if offset:
timezone = get_fixed_timezone(offset)
query = observation_query(
station_codes=station_codes,
interval=interval,
period=period,
year=year,
)
with engine.connect() as c:
results = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0],
result=i[2],
group_by=i[1] if len(i) > 1 else None) for i in results
]
if len(stats) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Station stats not found",
)
result = stats_factory(
stats=stats,
units=units,
interval=interval,
period=period,
code="bom",
group_field="temperature",
)
return result
def generate_weekly_export_map() -> StatMetadata:
"""
Generate export map for weekly power series
@TODO deconstruct this into separate methods and schema
ex. network.get_scada_range(), network_region.get_bom_station() etc.
"""
session = get_scoped_session()
networks = session.query(Network).filter(
Network.export_set.is_(True)).all()
if not networks:
raise Exception("No networks")
countries = list(set([network.country for network in networks]))
_exmap = []
# Loop countries
for country in countries:
# @TODO derive this
scada_range = get_scada_range(network=NetworkAU,
networks=[NetworkNEM, NetworkWEM])
if not scada_range:
raise Exception("Require a scada range for NetworkAU")
for year, week in week_series(scada_range.end, scada_range.start):
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.history,
country=country,
network=NetworkAU,
networks=[NetworkNEM, NetworkWEM],
year=year,
week=week,
date_range=date_range_from_week(year, week, NetworkAU),
interval=human_to_interval("30m"),
period=human_to_period("7d"),
)
_exmap.append(export)
# Loop networks
for network in networks:
network_schema = network_from_network_code(network.code)
scada_range = get_scada_range(network=network_schema)
if not scada_range:
raise Exception("Require a scada range for network: {}".format(
network.code))
for year, week in week_series(scada_range.end, scada_range.start):
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.history,
country=network.country,
network=network_schema,
year=year,
week=week,
date_range=date_range_from_week(year, week, NetworkAU),
interval=human_to_interval(f"{network.interval_size}m"),
period=human_to_period("7d"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
# Skip cases like wem/wem where region is supurfelous
if len(network.regions) < 2:
continue
for region in network.regions:
scada_range = get_scada_range(network=network_schema,
network_region=region.code)
if not scada_range:
logger.error(
"Require a scada range for network {} and region {}".
format(network_schema.code, region.code))
continue
for year, week in week_series(scada_range.end, scada_range.start):
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.history,
country=network.country,
network=network_schema,
year=year,
week=week,
date_range=date_range_from_week(
year, week, network_from_network_code(network.code)),
interval=human_to_interval(f"{network.interval_size}m"),
period=human_to_period("7d"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
export_meta = StatMetadata(date_created=datetime.now(),
version=get_version(),
resources=_exmap)
return export_meta
def export_energy(
stats: List[StatExport] = None,
priority: Optional[PriorityType] = None,
latest: Optional[bool] = False,
) -> None:
"""
Export energy stats from the export map
"""
if not stats:
export_map = get_export_map().get_by_stat_type(StatType.energy)
if priority:
export_map = export_map.get_by_priority(priority)
stats = export_map.resources
CURRENT_YEAR = datetime.now().year
logger.info(f"Running export_energy with {len(stats)} stats")
for energy_stat in stats:
if energy_stat.stat_type != StatType.energy:
continue
# @FIX trim to NEM since it's the one with the shortest
# data time span.
# @TODO find a better and more flexible way to do this in the
# range method
date_range_networks = energy_stat.networks or []
if NetworkNEM in date_range_networks:
date_range_networks = [NetworkNEM]
date_range: ScadaDateRange = get_scada_range(
network=energy_stat.network,
networks=date_range_networks,
energy=True)
if not date_range:
logger.error(
"Skipping - Could not get date range for energy {} {}".format(
energy_stat.network, date_range_networks))
continue
logger.debug("Date range is: {} {} => {}".format(
energy_stat.network.code, date_range.start, date_range.end))
# Migrate to this time_series
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
network=energy_stat.network,
year=energy_stat.year,
interval=energy_stat.interval,
period=human_to_period("1Y"),
)
if energy_stat.year:
if latest and energy_stat.year != CURRENT_YEAR:
continue
stat_set = energy_fueltech_daily(
time_series=time_series,
networks_query=energy_stat.networks,
network_region_code=energy_stat.network_region_query
or energy_stat.network_region,
)
if not stat_set:
continue
demand_energy_and_value = demand_network_region_daily(
time_series=time_series,
network_region_code=energy_stat.network_region,
networks=energy_stat.networks)
stat_set.append_set(demand_energy_and_value)
# Hard coded to NEM only atm but we'll put has_interconnectors
# in the metadata to automate all this
if energy_stat.network == NetworkNEM and energy_stat.network_region:
interconnector_flows = energy_interconnector_flows_and_emissions(
time_series=time_series,
networks_query=energy_stat.networks,
network_region_code=energy_stat.network_region_query
or energy_stat.network_region,
)
stat_set.append_set(interconnector_flows)
if energy_stat.bom_station:
try:
weather_stats = weather_daily(
time_series=time_series,
station_code=energy_stat.bom_station,
network_region=energy_stat.network_region,
)
stat_set.append_set(weather_stats)
except NoResults as e:
logger.info("No results for weather result: {}".format(e))
except Exception as e:
logger.error("weather_stat exception: {}".format(e))
pass
else:
logger.info("Stat set has no bom station")
write_output(energy_stat.path, stat_set)
elif energy_stat.period and energy_stat.period.period_human == "all" and not latest:
time_series.period = human_to_period("all")
time_series.interval = human_to_interval("1M")
time_series.year = None
stat_set = energy_fueltech_daily(
time_series=time_series,
networks_query=energy_stat.networks,
network_region_code=energy_stat.network_region_query
or energy_stat.network_region,
)
if not stat_set:
continue
demand_energy_and_value = demand_network_region_daily(
time_series=time_series,
network_region_code=energy_stat.network_region,
networks=energy_stat.networks)
stat_set.append_set(demand_energy_and_value)
# Hard coded to NEM only atm but we'll put has_interconnectors
# in the metadata to automate all this
if energy_stat.network == NetworkNEM and energy_stat.network_region:
interconnector_flows = energy_interconnector_flows_and_emissions(
time_series=time_series,
networks_query=energy_stat.networks,
network_region_code=energy_stat.network_region_query
or energy_stat.network_region,
)
stat_set.append_set(interconnector_flows)
if energy_stat.bom_station:
try:
weather_stats = weather_daily(
time_series=time_series,
station_code=energy_stat.bom_station,
network_region=energy_stat.network_region,
)
stat_set.append_set(weather_stats)
except NoResults as e:
logger.info("No weather results: {}".format(e))
except Exception:
pass
write_output(energy_stat.path, stat_set)
def export_all_daily(
networks: List[NetworkSchema] = [NetworkNEM, NetworkWEM],
network_region_code: Optional[str] = None,
) -> None:
session = get_scoped_session()
cpi = gov_stats_cpi()
for network in networks:
network_regions = session.query(NetworkRegion).filter_by(
export_set=True).filter_by(network_id=network.code)
if network_region_code:
network_regions = network_regions.filter_by(
code=network_region_code)
network_regions = network_regions.all()
for network_region in network_regions:
logging.info("Exporting for network {} and region {}".format(
network.code, network_region.code))
networks = [
NetworkNEM, NetworkAEMORooftop, NetworkAEMORooftopBackfill
]
if network_region.code == "WEM":
networks = [NetworkWEM, NetworkAPVI]
scada_range: ScadaDateRange = get_scada_range(network=network,
networks=networks,
energy=True)
if not scada_range or not scada_range.start:
logger.error(
"Could not get scada range for network {} and energy {}".
format(network, True))
continue
time_series = TimeSeries(
start=scada_range.start,
end=scada_range.end,
network=network,
interval=human_to_interval("1d"),
period=human_to_period("all"),
)
stat_set = energy_fueltech_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
if not stat_set:
continue
demand_energy_and_value = demand_network_region_daily(
time_series=time_series,
network_region_code=network_region.code,
networks=networks)
stat_set.append_set(demand_energy_and_value)
# Hard coded to NEM only atm but we'll put has_interconnectors
# in the metadata to automate all this
if network == NetworkNEM:
interconnector_flows = energy_interconnector_flows_and_emissions(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_flows)
bom_station = get_network_region_weather_station(
network_region.code)
if bom_station:
try:
weather_stats = weather_daily(
time_series=time_series,
station_code=bom_station,
network_region=network_region.code,
)
stat_set.append_set(weather_stats)
except Exception:
pass
if cpi:
stat_set.append_set(cpi)
write_output(f"v3/stats/au/{network_region.code}/daily.json",
stat_set)
def energy_network_fueltech_api(
network_code: str = Query(None, description="Network code"),
network_region: str = Query(None, description="Network region"),
interval_human: str = Query("1d", description="Interval"),
year: int = Query(None, description="Year to query"),
period_human: str = Query("1Y", description="Period"),
engine=Depends(get_database_engine),
) -> OpennemDataSet:
network = network_from_network_code(network_code)
interval = human_to_interval(interval_human)
period_obj: TimePeriod = human_to_period("1Y")
if period_human:
period_obj = human_to_period(period_human)
units = get_unit("energy_giga")
query = ""
if year and isinstance(year, int):
period_obj = human_to_period("1Y")
if year > datetime.now().year or year < 1996:
raise HTTPException(
status_code=status.HTTP_406_NOT_ACCEPTABLE,
detail="Not a valid year",
)
scada_range = get_scada_range(network=network)
query = energy_network_fueltech_year(
network=network,
interval=interval,
year=year,
network_region=network_region,
scada_range=scada_range,
)
elif period_obj and period_obj.period_human == "all":
scada_range = get_scada_range(network=network)
query = energy_network_fueltech_all(
network=network,
network_region=network_region,
scada_range=scada_range,
)
else:
query = energy_network_fueltech(
network=network,
interval=interval,
period=period_obj,
network_region=network_region,
)
# print(query)
with engine.connect() as c:
results = list(c.execute(query))
stats = [
DataQueryResult(interval=i[0], result=i[1], group_by=i[2] if len(i) > 1 else None)
for i in results
]
if len(stats) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Energy stats not found",
)
result = stats_factory(
stats,
code=network.code,
network=network,
interval=interval,
period=period_obj,
units=units,
region=network_region,
fueltech_group=True,
)
if not result:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="No stats")
return result
def price_network_endpoint(
engine: Engine = Depends(get_database_engine),
network_code: str = Path(..., description="Network code"),
network_region: Optional[str] = Query(None, description="Network region code"),
forecasts: bool = Query(False, description="Include price forecasts"),
) -> OpennemDataSet:
"""Returns network and network region price info for interval which defaults to network
interval size
Args:
engine ([type], optional): Database engine. Defaults to Depends(get_database_engine).
Raises:
HTTPException: No results
Returns:
OpennemData: data set
"""
engine = get_database_engine()
network = None
try:
network = network_from_network_code(network_code)
except Exception:
raise HTTPException(detail="Network not found", status_code=status.HTTP_404_NOT_FOUND)
interval_obj = human_to_interval("5m")
period_obj = human_to_period("1d")
scada_range = get_balancing_range(network=network, include_forecasts=forecasts)
if not scada_range:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Could not find a date range",
)
if not network:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Network not found",
)
time_series = TimeSeries(
start=scada_range.start,
network=network,
interval=interval_obj,
period=period_obj,
)
if network_region:
time_series.network.regions = [NetworkNetworkRegion(code=network_region)]
query = network_region_price_query(time_series=time_series)
with engine.connect() as c:
logger.debug(query)
row = list(c.execute(query))
if len(row) < 1:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
result_set = [
DataQueryResult(interval=i[0], result=i[3], group_by=i[2] if len(i) > 1 else None)
for i in row
]
result = stats_factory(
result_set,
network=time_series.network,
period=time_series.period,
interval=time_series.interval,
units=get_unit("price"),
group_field="price",
include_group_code=True,
include_code=True,
)
if not result or not result.data:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No results",
)
return result
@pytest.mark.parametrize(
[
"ts", "start_expected", "end_expected", "interval_expected",
"length_expected"
],
[
# Test 1 hour inclusive
(
TimeSeries(
start=datetime.fromisoformat("2021-01-15 12:00:00+00:00"),
end=datetime.fromisoformat("2021-01-15 13:00:00+00:00"),
network=NetworkNEM,
interval=NetworkNEM.get_interval(),
period=human_to_period("1h"),
),
# Also testing timezone shift from UTC to NEM time
datetime.fromisoformat("2021-01-15 22:00:00+10:00"),
datetime.fromisoformat("2021-01-15 23:00:00+10:00"),
"5m",
13, # number of 5 minute intervals in an hour _inclusive_
),
# Test 1 week inclusive
(
TimeSeries(
start=datetime.fromisoformat("1997-05-05 12:45:00+00:00"),
end=datetime.fromisoformat("2021-01-15 12:45:00+00:00"),
network=NetworkNEM,
interval=NetworkNEM.get_interval(),
period=human_to_period("7d"),
def get_export_map() -> StatMetadata:
"""
Generates a map of all export JSONs
"""
session = SessionLocal()
networks = session.query(Network).filter(Network.export_set.is_(True)).all()
if not networks:
raise Exception("No networks")
countries = list(set([network.country for network in networks]))
_exmap = []
for country in countries:
# @TODO derive this
scada_range = get_scada_range(network=NetworkAU, networks=[NetworkNEM, NetworkWEM])
if not scada_range:
raise Exception("Require a scada range")
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.live,
country=country,
date_range=scada_range,
network=NetworkAU,
networks=[NetworkNEM, NetworkWEM],
interval=NetworkAU.get_interval(),
period=human_to_period("7d"),
)
_exmap.append(export)
for year in range(
datetime.now().year,
scada_range.start.year - 1,
-1,
):
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.daily,
country=country,
date_range=scada_range,
network=NetworkAU,
networks=[NetworkNEM, NetworkWEM],
year=year,
interval=human_to_interval("1d"),
period=human_to_period("1Y"),
)
_exmap.append(export)
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.monthly,
country=country,
date_range=scada_range,
network=NetworkAU,
networks=[NetworkNEM, NetworkWEM],
interval=human_to_interval("1M"),
period=human_to_period("all"),
)
_exmap.append(export)
for network in networks:
network_schema = network_from_network_code(network.code)
scada_range = get_scada_range(network=network_schema)
bom_station = get_network_region_weather_station(network.code)
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.live,
country=network.country,
date_range=scada_range,
network=network_schema,
bom_station=bom_station,
interval=network_schema.get_interval(),
period=human_to_period("7d"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
if not scada_range:
raise Exception("Require a scada range")
for year in range(
datetime.now().year,
scada_range.start.year - 1,
-1,
):
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.daily,
country=network.country,
date_range=scada_range,
network=network_schema,
bom_station=bom_station,
year=year,
period=human_to_period("1Y"),
interval=human_to_interval("1d"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.monthly,
country=network.country,
date_range=scada_range,
network=network_schema,
bom_station=bom_station,
interval=human_to_interval("1M"),
period=human_to_period("all"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
# Skip cases like wem/wem where region is supurfelous
if len(network.regions) < 2:
continue
for region in network.regions:
scada_range = get_scada_range(network=network_schema, network_region=region)
bom_station = get_network_region_weather_station(region.code)
if not scada_range:
raise Exception("Require a scada range")
export = StatExport(
stat_type=StatType.power,
priority=PriorityType.live,
country=network.country,
date_range=scada_range,
network=network_schema,
network_region=region.code,
bom_station=bom_station,
period=human_to_period("7d"),
interval=network_schema.get_interval(),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
for year in range(
datetime.now().year,
scada_range.start.year - 1,
-1,
):
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.daily,
country=network.country,
date_range=scada_range,
network=network_schema,
network_region=region.code,
bom_station=bom_station,
year=year,
period=human_to_period("1Y"),
interval=human_to_interval("1d"),
)
_exmap.append(export)
export = StatExport(
stat_type=StatType.energy,
priority=PriorityType.monthly,
country=network.country,
date_range=scada_range,
network=network_schema,
network_region=region.code,
bom_station=bom_station,
period=human_to_period("all"),
interval=human_to_interval("1M"),
)
if network.code == "WEM":
export.networks = [NetworkWEM, NetworkAPVI]
export.network_region_query = "WEM"
_exmap.append(export)
export_meta = StatMetadata(
date_created=datetime.now(), version=get_version(), resources=_exmap
)
return export_meta