Run black and isort

src/egon/data/datasets/DSM_cts_ind.py

@@ -783,7 +783,6 @@ def dsm_cts_ind(
         ind_cool_vent_share=0.039,
         ind_vent_share=0.017,
     ):
-
         """
         Execute methodology to create and implement components for DSM considering
         a) CTS per osm-area: combined potentials of cooling, ventilation and air conditioning

src/egon/data/datasets/chp/__init__.py

@@ -3,13 +3,16 @@
 (CHP) plants.
 """
 
+from pathlib import Path
+
 from geoalchemy2 import Geometry
 from shapely.ops import nearest_points
 from sqlalchemy import Boolean, Column, Float, Integer, Sequence, String
 from sqlalchemy.dialects.postgresql import JSONB
 from sqlalchemy.ext.declarative import declarative_base
 import geopandas as gpd
 import pandas as pd
+import pypsa
 
 from egon.data import config, db
 from egon.data.datasets import Dataset
@@ -18,6 +21,7 @@
     assign_use_case,
     existing_chp_smaller_10mw,
     extension_per_federal_state,
+    extension_to_areas,
     select_target,
 )
 from egon.data.datasets.power_plants import (
@@ -26,9 +30,6 @@
     filter_mastr_geometry,
     scale_prox2now,
 )
-import pypsa
-from egon.data.datasets.chp.small_chp import extension_to_areas
-from pathlib import Path
 
 Base = declarative_base()
 

src/egon/data/datasets/electrical_neighbours.py

@@ -3,17 +3,17 @@
 
 import zipfile
 
-import geopandas as gpd
-import pandas as pd
 from shapely.geometry import LineString
 from sqlalchemy.orm import sessionmaker
+import geopandas as gpd
+import pandas as pd
 
-import egon.data.datasets.etrago_setup as etrago
-import egon.data.datasets.scenario_parameters.parameters as scenario_parameters
 from egon.data import config, db
 from egon.data.datasets import Dataset
 from egon.data.datasets.fill_etrago_gen import add_marginal_costs
 from egon.data.datasets.scenario_parameters import get_sector_parameters
+import egon.data.datasets.etrago_setup as etrago
+import egon.data.datasets.scenario_parameters.parameters as scenario_parameters
 
 
 class ElectricalNeighbours(Dataset):
@@ -1082,9 +1082,12 @@ def insert_storage(capacities, session=None):
     )
 
     # Add columns for additional parameters to df
-    store["dispatch"], store["store"], store["standing_loss"], store[
-        "max_hours"
-    ] = (None, None, None, None)
+    (
+        store["dispatch"],
+        store["store"],
+        store["standing_loss"],
+        store["max_hours"],
+    ) = (None, None, None, None)
 
     # Insert carrier specific parameters
 

src/egon/data/datasets/power_plants/__init__.py

@@ -1,14 +1,7 @@
 """The central module containing all code dealing with power plant data.
 """
 from geoalchemy2 import Geometry
-from sqlalchemy import (
-    BigInteger,
-    Column,
-    Float,
-    Integer,
-    Sequence,
-    String,
-)
+from sqlalchemy import BigInteger, Column, Float, Integer, Sequence, String
 from sqlalchemy.dialects.postgresql import JSONB
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.orm import sessionmaker

src/egon/data/datasets/renewable_feedin.py

@@ -491,7 +491,7 @@ def heat_pump_cop():
 
     # Calculate coefficient of performance for air sourced heat pumps
     # according to Brown et. al
-    cop = 6.81 - 0.121 * delta_t + 0.00063 * delta_t ** 2
+    cop = 6.81 - 0.121 * delta_t + 0.00063 * delta_t**2
 
     df = pd.DataFrame(
         index=temperature.to_pandas().index,

src/egon/data/datasets/scenario_capacities.py

@@ -84,7 +84,6 @@ def create_table():
 
 
 def nuts_mapping():
-
     nuts_mapping = {
         "BW": "DE1",
         "NW": "DEA",
@@ -157,13 +156,15 @@ def insert_capacities_per_federal_state_nep():
     df_windoff = pd.read_excel(
         target_file,
         sheet_name="WInd_Offshore_NEP",
-    ).dropna(subset=['Bundesland', 'Netzverknuepfungspunkt'])
+    ).dropna(subset=["Bundesland", "Netzverknuepfungspunkt"])
 
     # Remove trailing whitespace from column Bundesland
-    df_windoff['Bundesland']= df_windoff['Bundesland'].str.strip()
+    df_windoff["Bundesland"] = df_windoff["Bundesland"].str.strip()
 
     # Group and sum capacities per federal state
-    df_windoff_fs = df_windoff[['Bundesland', 'C 2035']].groupby(['Bundesland']).sum()
+    df_windoff_fs = (
+        df_windoff[["Bundesland", "C 2035"]].groupby(["Bundesland"]).sum()
+    )
 
     # List federal state with an assigned wind offshore capacity
     index_list = list(df_windoff_fs.index.values)
@@ -172,9 +173,9 @@ def insert_capacities_per_federal_state_nep():
     # df_windoff_fs
 
     for state in index_list:
-
-        df.at['Wind offshore', state] = df_windoff_fs.at[state, 'C 2035']/1000
-
+        df.at["Wind offshore", state] = (
+            df_windoff_fs.at[state, "C 2035"] / 1000
+        )
 
     # sort NEP-carriers:
     rename_carrier = {
@@ -216,7 +217,6 @@ def insert_capacities_per_federal_state_nep():
     ]
 
     for bl in map_nuts.index:
-
         data = pd.DataFrame(df[bl])
 
         # if distribution to federal states is not provided,
@@ -687,7 +687,9 @@ def eGon100_capacities():
                             df.p_nom[f"residential_{merge_carrier}"]
                             + df.p_nom[f"services_{merge_carrier}"]
                         ),
-                        "component": df.component[f"residential_{merge_carrier}"],
+                        "component": df.component[
+                            f"residential_{merge_carrier}"
+                        ],
                     },
                 )
             )

src/egon/data/datasets/storages/__init__.py

@@ -1,25 +1,25 @@
 """The central module containing all code dealing with power plant data.
 """
-from geoalchemy2 import Geometry
 from pathlib import Path
+
+from geoalchemy2 import Geometry
 from sqlalchemy import BigInteger, Column, Float, Integer, Sequence, String
 from sqlalchemy.dialects.postgresql import JSONB
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.orm import sessionmaker
-from egon.data.datasets.storages.pumped_hydro import (
-    select_mastr_pumped_hydro,
-    select_nep_pumped_hydro,
-    match_storage_units,
-    get_location,
-    apply_voltage_level_thresholds,
-)
-from egon.data.datasets.power_plants import assign_voltage_level
 import geopandas as gpd
 import pandas as pd
 
-from egon.data import db, config
+from egon.data import config, db
 from egon.data.datasets import Dataset
-
+from egon.data.datasets.power_plants import assign_voltage_level
+from egon.data.datasets.storages.pumped_hydro import (
+    apply_voltage_level_thresholds,
+    get_location,
+    match_storage_units,
+    select_mastr_pumped_hydro,
+    select_nep_pumped_hydro,
+)
 
 Base = declarative_base()
 
@@ -353,9 +353,9 @@ def home_batteries_per_scenario(scenario):
             sheet_name="1.Entwurf_NEP2035_V2021",
             index_col="Unnamed: 0",
         )
-        
-    # Select target value in MW
-        target = capacities_nep.Summe["PV-Batteriespeicher"]*1000
+
+        # Select target value in MW
+        target = capacities_nep.Summe["PV-Batteriespeicher"] * 1000
 
     else:
         target = db.select_dataframe(