apply ruff linting

scripts/add_existing_baseyear.py

@@ -63,7 +63,7 @@ def add_existing_renewables(df_agg, costs):
     """
     tech_map = {"solar": "PV", "onwind": "Onshore", "offwind": "Offshore"}
 
-    countries = snakemake.config["countries"]
+    countries = snakemake.config["countries"]  # noqa: F841
     irena = pm.data.IRENASTAT().powerplant.convert_country_to_alpha2()
     irena = irena.query("Country in @countries")
     irena = irena.groupby(["Technology", "Country", "Year"]).Capacity.sum()
@@ -440,8 +440,6 @@ def add_heating_capacities_installed_before_baseyear(
         snakemake.input.existing_heating_distribution, header=[0, 1], index_col=0
     )
 
-    techs = existing_heating.columns.get_level_values(1).unique()
-
     for name in existing_heating.columns.get_level_values(0).unique():
         name_type = "central" if name == "urban central" else "decentral"
 

scripts/base_network.py

@@ -896,7 +896,7 @@ def build_bus_shapes(n, country_shapes, offshore_shapes, countries):
 
     shapes = pd.concat(onshore_regions, ignore_index=True)
 
-    return onshore_regions, offshore_regions, shapes
+    return onshore_regions, offshore_regions, shapes, offshore_shapes
 
 
 def append_bus_shapes(n, shapes, type):
@@ -950,7 +950,7 @@ def append_bus_shapes(n, shapes, type):
         snakemake.config,
     )
 
-    onshore_regions, offshore_regions, shapes = build_bus_shapes(
+    onshore_regions, offshore_regions, shapes, offshore_shapes = build_bus_shapes(
         n,
         snakemake.input.country_shapes,
         snakemake.input.offshore_shapes,

scripts/build_biomass_potentials.py

@@ -13,10 +13,11 @@
 import numpy as np
 import pandas as pd
 
+from _helpers import configure_logging, set_scenario_config
+
 logger = logging.getLogger(__name__)
 AVAILABLE_BIOMASS_YEARS = [2010, 2020, 2030, 2040, 2050]
 
-from _helpers import configure_logging, set_scenario_config
 
 
 def build_nuts_population_data(year=2013):

scripts/build_energy_totals.py

@@ -124,7 +124,6 @@ def build_eurostat(input_eurostat, countries, nprocesses=1, disable_progressbar=
     df = pd.concat([temp, df.loc[~int_avia]])
 
     # Fill in missing data on "Domestic aviation" for each country.
-    domestic_avia = df.index.get_level_values(4) == "Domestic aviation"
     for country in countries:
         slicer = idx[country, :, :, :, "Domestic aviation"]
         # For the Total and Fossil energy columns, fill in zeros with

scripts/build_existing_heating_distribution.py

@@ -55,7 +55,6 @@ def build_existing_heating():
     nodal_heating = nodal_heating.multiply(pop_layout.fraction, axis=0)
 
     district_heat_info = pd.read_csv(snakemake.input.district_heat_share, index_col=0)
-    dist_fraction = district_heat_info["district fraction of node"]
     urban_fraction = district_heat_info["urban fraction"]
 
     energy_layout = pd.read_csv(

scripts/retrieve_electricity_demand.py

@@ -10,10 +10,10 @@
 
 import pandas as pd
 
-logger = logging.getLogger(__name__)
-
 from _helpers import configure_logging, set_scenario_config
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake

scripts/solve_network.py

@@ -693,7 +693,6 @@ def add_BAU_constraints(n, config):
     ext_i = n.generators.query("p_nom_extendable")
     ext_carrier_i = xr.DataArray(ext_i.carrier.rename_axis("Generator-ext"))
     lhs = p_nom.groupby(ext_carrier_i).sum()
-    index = mincaps.index.intersection(lhs.indexes["carrier"])
     rhs = mincaps[lhs.indexes["carrier"]].rename_axis("carrier")
     n.model.add_constraints(lhs >= rhs, name="bau_mincaps")
 

scripts/time_aggregation.py

@@ -47,6 +47,7 @@
 import pandas as pd
 import pypsa
 import xarray as xr
+import tsam.timeseriesaggregation as tsam
 from _helpers import (
     configure_logging,
     set_scenario_config,