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 export_metadata() -> bool:
"""
Export metadata
"""
_export_map_out = get_export_map()
# this is a hack because pydantic doesn't
# serialize properties
for r in _export_map_out.resources:
r.file_path = r.path
wrote_bytes = write_output("metadata.json", _export_map_out)
if wrote_bytes and wrote_bytes > 0:
return True
return False
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 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 export_power(
stats: List[StatExport] = None,
priority: Optional[PriorityType] = None,
latest: Optional[bool] = False,
) -> None:
"""
Export power stats from the export map
"""
# Not passed a stat map so go and get one
if not stats:
export_map = None
if priority and priority == PriorityType.history:
export_map = get_weekly_export_map()
else:
export_map = get_export_map().get_by_stat_type(StatType.power)
if priority:
export_map = export_map.get_by_priority(priority)
stats = export_map.resources
output_count: int = 0
logger.info("Running {}export {} with {} stats".format(
"latest " if latest else "", priority, len(stats)))
for power_stat in stats:
if power_stat.stat_type != StatType.power:
continue
if output_count >= 1 and latest:
return None
date_range_networks = power_stat.networks or []
if NetworkNEM in date_range_networks:
date_range_networks = [NetworkNEM]
date_range: ScadaDateRange = get_scada_range(
network=power_stat.network, networks=date_range_networks)
logger.debug("Date range for {}: {} => {}".format(
power_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=power_stat.network,
year=power_stat.year,
interval=power_stat.interval,
period=power_stat.period,
)
stat_set = power_week(
time_series=time_series,
network_region_code=power_stat.network_region_query
or power_stat.network_region,
networks_query=power_stat.networks,
)
if not stat_set:
logger.info("No power stat set for {} {} {}".format(
power_stat.period,
power_stat.networks,
power_stat.network_region,
))
continue
demand_set = demand_week(
time_series=time_series,
networks_query=power_stat.networks,
network_region_code=power_stat.network_region_query
or power_stat.network_region,
)
stat_set.append_set(demand_set)
if power_stat.network_region:
flow_set = power_flows_region_week(
time_series=time_series,
network_region_code=power_stat.network_region,
)
if flow_set:
stat_set.append_set(flow_set)
time_series_weather = time_series.copy()
time_series_weather.interval = human_to_interval("30m")
if power_stat.bom_station:
try:
weather_set = weather_daily(
time_series=time_series_weather,
station_code=power_stat.bom_station,
network_region=power_stat.network_region,
include_min_max=False,
unit_name="temperature",
)
stat_set.append_set(weather_set)
except Exception:
pass
write_output(power_stat.path, stat_set)
output_count += 1
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_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 export_all_daily() -> None:
session = SessionLocal()
network_regions = session.query(NetworkRegion).all()
cpi = gov_stats_cpi()
for network_region in network_regions:
network = network_from_network_code(network_region.network.code)
networks = None
if network_region.code == "WEM":
networks = [NetworkWEM, NetworkAPVI]
scada_range: ScadaDateRange = get_scada_range(network=network,
networks=networks)
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
# 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_region_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_flows)
interconnector_emissions = energy_interconnector_emissions_region_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_emissions)
bom_station = get_network_region_weather_station(network_region.code)
if bom_station:
weather_stats = weather_daily(
time_series=time_series,
station_code=bom_station,
network_region=network_region.code,
)
stat_set.append_set(weather_stats)
if cpi:
stat_set.append_set(cpi)
write_output(f"v3/stats/au/{network_region.code}/daily.json", stat_set)
def export_all_monthly() -> None:
session = SessionLocal()
network_regions = session.query(NetworkRegion).all()
all_monthly = OpennemDataSet(code="au",
data=[],
version=get_version(),
created_at=datetime.now())
cpi = gov_stats_cpi()
all_monthly.append_set(cpi)
for network_region in network_regions:
network = network_from_network_code(network_region.network.code)
networks = None
if network_region.code == "WEM":
networks = [NetworkWEM, NetworkAPVI]
scada_range: ScadaDateRange = get_scada_range(network=network,
networks=networks)
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
if network == NetworkNEM:
interconnector_flows = energy_interconnector_region_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_flows)
interconnector_emissions = energy_interconnector_emissions_region_daily(
time_series=time_series,
networks_query=networks,
network_region_code=network_region.code,
)
stat_set.append_set(interconnector_emissions)
all_monthly.append_set(stat_set)
bom_station = get_network_region_weather_station(network_region.code)
if bom_station:
weather_stats = weather_daily(
time_series=time_series,
station_code=bom_station,
network_region=network_region.code,
)
all_monthly.append_set(weather_stats)
write_output("v3/stats/au/all/monthly.json", all_monthly)
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
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)
# 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
# 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_region_daily(
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)
interconnector_emissions = energy_interconnector_emissions_region_daily(
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_emissions)
if energy_stat.bom_station:
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)
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
# 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_region_daily(
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)
interconnector_emissions = energy_interconnector_emissions_region_daily(
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_emissions)
if energy_stat.bom_station:
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)
stat_set = pad_stat_set(stat_set)
write_output(energy_stat.path, stat_set)
def export_network_intervals_for_week(
week_start: datetime,
week_end: datetime,
network: NetworkSchema,
network_region: NetworkRegion,
) -> int | None:
""" """
week_number = get_week_number_from_datetime(week_start)
logging.info(
"Exporting historic intervals for network {} and region {} and year {} and week {} ({} => {})"
.format(network.code, network_region.code, week_start.year,
week_number, week_start, week_end))
time_series = TimeSeries(
start=week_start,
end=week_end + timedelta(days=1),
network=network,
interval=network.get_interval(),
period=human_to_period("7d"),
)
stat_set = power_week(
time_series=time_series,
networks_query=network.get_networks_query(),
network_region_code=network_region.code,
)
if not stat_set:
return None
# emissions for network
emission_intervals = emissions_for_network_interval(
time_series=time_series, network_region_code=network_region.code)
stat_set.append_set(emission_intervals)
# demand and pricing
demand_energy_and_value = demand_network_region_daily(
time_series=time_series,
network_region_code=network_region.code,
networks=network.get_networks_query())
stat_set.append_set(demand_energy_and_value)
if network == NetworkNEM:
interconnector_flows = energy_interconnector_flows_and_emissions(
time_series=time_series,
networks_query=network.get_networks_query(),
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
save_path = (
f"v3/stats/historic/weekly/{network.code}/{network_region.code}/year/{week_start.year}/week/{week_number}.json"
)
written_bytes = write_output(save_path, stat_set)
return written_bytes
def export_power(
stats: List[StatExport] = None,
priority: Optional[PriorityType] = None,
latest: Optional[bool] = False,
) -> None:
"""
Export power stats from the export map
"""
if not stats:
export_map = get_export_map().get_by_stat_type(StatType.power)
if priority:
export_map = export_map.get_by_priority(priority)
stats = export_map.resources
output_count: int = 0
for power_stat in stats:
if power_stat.stat_type != StatType.power:
continue
if output_count >= 1 and latest:
return None
date_range_networks = power_stat.networks or []
if NetworkNEM in date_range_networks:
date_range_networks = [NetworkNEM]
date_range: ScadaDateRange = get_scada_range(
network=power_stat.network, networks=date_range_networks)
# Migrate to this time_series
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
network=power_stat.network,
year=power_stat.year,
interval=power_stat.interval,
period=power_stat.period,
)
stat_set = power_week(
time_series=time_series,
network_region_code=power_stat.network_region_query
or power_stat.network_region,
networks_query=power_stat.networks,
)
if not stat_set:
logger.info("No power stat set for {} {} {}".format(
power_stat.period,
power_stat.networks,
power_stat.network_region,
))
continue
demand_set = demand_week(
time_series=time_series,
networks_query=power_stat.networks,
network_region_code=power_stat.network_region_query
or power_stat.network_region,
)
stat_set.append_set(demand_set)
if power_stat.network_region:
flow_set = power_flows_week(
time_series=time_series,
network_region_code=power_stat.network_region,
)
if flow_set:
stat_set.append_set(flow_set)
if power_stat.bom_station:
weather_set = weather_daily(
time_series=time_series,
station_code=power_stat.bom_station,
network_region=power_stat.network_region,
include_min_max=False,
unit_name="temperature",
)
stat_set.append_set(weather_set)
write_output(power_stat.path, stat_set)
output_count += 1
