fix import order

scripts/_benchmark.py

@@ -13,15 +13,15 @@ import os
 import sys
 import time
 
+from memory_profiler import _get_memory, choose_backend
+
 logger = logging.getLogger(__name__)
 
 # TODO: provide alternative when multiprocessing is not available
 try:
     from multiprocessing import Pipe, Process
 except ImportError:
-    from multiprocessing.dummy import Process, Pipe
+    from multiprocessing.dummy import Pipe, Process
-
-from memory_profiler import _get_memory, choose_backend
 
 
 # The memory logging facilities have been adapted from memory_profiler

scripts/add_brownfield.py

@@ -8,17 +8,15 @@ Prepares brownfield data from previous planning horizon.
 
 import logging
 
-logger = logging.getLogger(__name__)
-
-import pandas as pd
-
-idx = pd.IndexSlice
-
 import numpy as np
+import pandas as pd
 import pypsa
 from _helpers import update_config_with_sector_opts
 from add_existing_baseyear import add_build_year_to_new_assets
 
+logger = logging.getLogger(__name__)
+idx = pd.IndexSlice
+
 
 def add_brownfield(n, n_p, year):
     logger.info(f"Preparing brownfield for the year {year}")

scripts/add_existing_baseyear.py

@@ -8,25 +8,20 @@ horizon.
 """
 
 import logging
-
-logger = logging.getLogger(__name__)
-
-import pandas as pd
-
-idx = pd.IndexSlice
-
 from types import SimpleNamespace
 
 import country_converter as coco
 import numpy as np
+import pandas as pd
 import pypsa
 import xarray as xr
 from _helpers import update_config_with_sector_opts
 from add_electricity import sanitize_carriers
 from prepare_sector_network import cluster_heat_buses, define_spatial, prepare_costs
 
+logger = logging.getLogger(__name__)
 cc = coco.CountryConverter()
-
+idx = pd.IndexSlice
 spatial = SimpleNamespace()
 
 

scripts/build_biomass_potentials.py

@@ -9,11 +9,11 @@ using data from JRC ENSPRESO.
 
 import logging
 
-logger = logging.getLogger(__name__)
 import geopandas as gpd
 import numpy as np
 import pandas as pd
 
+logger = logging.getLogger(__name__)
 AVAILABLE_BIOMASS_YEARS = [2010, 2020, 2030, 2040, 2050]
 
 

scripts/build_electricity_demand.py

@@ -41,12 +41,13 @@ Outputs
 
 import logging
 
-logger = logging.getLogger(__name__)
 import numpy as np
 import pandas as pd
 from _helpers import configure_logging
 from pandas import Timedelta as Delta
 
+logger = logging.getLogger(__name__)
+
 
 def load_timeseries(fn, years, countries, powerstatistics=True):
     """

scripts/build_energy_totals.py

@@ -7,9 +7,6 @@ Build total energy demands per country using JRC IDEES, eurostat, and EEA data.
 """
 
 import logging
-
-logger = logging.getLogger(__name__)
-
 import multiprocessing as mp
 from functools import partial
 
@@ -21,7 +18,7 @@ from _helpers import mute_print
 from tqdm import tqdm
 
 cc = coco.CountryConverter()
-
+logger = logging.getLogger(__name__)
 idx = pd.IndexSlice
 
 

scripts/build_gas_input_locations.py

@@ -9,12 +9,12 @@ production sites with data from SciGRID_gas and Global Energy Monitor.
 
 import logging
 
-logger = logging.getLogger(__name__)
-
 import geopandas as gpd
 import pandas as pd
 from cluster_gas_network import load_bus_regions
 
+logger = logging.getLogger(__name__)
+
 
 def read_scigrid_gas(fn):
     df = gpd.read_file(fn)

scripts/build_gas_network.py

@@ -9,13 +9,13 @@ Preprocess gas network based on data from bthe SciGRID_gas project
 
 import logging
 
-logger = logging.getLogger(__name__)
-
 import geopandas as gpd
 import pandas as pd
 from pypsa.geo import haversine_pts
 from shapely.geometry import Point
 
+logger = logging.getLogger(__name__)
+
 
 def diameter_to_capacity(pipe_diameter_mm):
     """

scripts/build_industrial_distribution_key.py

@@ -7,9 +7,6 @@ Build spatial distribution of industries from Hotmaps database.
 """
 
 import logging
-
-logger = logging.getLogger(__name__)
-
 import uuid
 from itertools import product
 
@@ -18,6 +15,7 @@ import geopandas as gpd
 import pandas as pd
 from packaging.version import Version, parse
 
+logger = logging.getLogger(__name__)
 cc = coco.CountryConverter()
 
 

scripts/build_industrial_production_per_country.py

@@ -7,11 +7,8 @@ Build industrial production per country.
 """
 
 import logging
-from functools import partial
-
-logger = logging.getLogger(__name__)
-
 import multiprocessing as mp
+from functools import partial
 
 import country_converter as coco
 import numpy as np
@@ -19,6 +16,7 @@ import pandas as pd
 from _helpers import mute_print
 from tqdm import tqdm
 
+logger = logging.getLogger(__name__)
 cc = coco.CountryConverter()
 
 tj_to_ktoe = 0.0238845

scripts/build_population_layouts.py

@@ -8,15 +8,14 @@ Build mapping between cutout grid cells and population (total, urban, rural).
 
 import logging
 
-logger = logging.getLogger(__name__)
-
-
 import atlite
 import geopandas as gpd
 import numpy as np
 import pandas as pd
 import xarray as xr
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake

scripts/cluster_gas_network.py

@@ -8,14 +8,14 @@ Cluster gas transmission network to clustered model regions.
 
 import logging
 
-logger = logging.getLogger(__name__)
-
 import geopandas as gpd
 import pandas as pd
 from packaging.version import Version, parse
 from pypsa.geo import haversine_pts
 from shapely import wkt
 
+logger = logging.getLogger(__name__)
+
 
 def concat_gdf(gdf_list, crs="EPSG:4326"):
     """

scripts/make_summary.py

@@ -8,9 +8,6 @@ capacity factors, curtailment, energy balances, prices and other metrics.
 """
 
 import logging
-
-logger = logging.getLogger(__name__)
-
 import sys
 
 import numpy as np
@@ -19,7 +16,7 @@ import pypsa
 from prepare_sector_network import prepare_costs
 
 idx = pd.IndexSlice
-
+logger = logging.getLogger(__name__)
 opt_name = {"Store": "e", "Line": "s", "Transformer": "s"}
 
 

scripts/plot_network.py

@@ -13,8 +13,6 @@ nodes.
 
 import logging
 
-logger = logging.getLogger(__name__)
-
 import cartopy.crs as ccrs
 import geopandas as gpd
 import matplotlib.pyplot as plt
@@ -24,6 +22,7 @@ from make_summary import assign_carriers
 from plot_summary import preferred_order, rename_techs
 from pypsa.plot import add_legend_circles, add_legend_lines, add_legend_patches
 
+logger = logging.getLogger(__name__)
 plt.style.use(["ggplot"])
 
 

scripts/plot_summary.py

@@ -8,12 +8,11 @@ Creates plots from summary CSV files.
 
 import logging
 
-logger = logging.getLogger(__name__)
-
 import matplotlib.gridspec as gridspec
 import matplotlib.pyplot as plt
 import pandas as pd
 
+logger = logging.getLogger(__name__)
 plt.style.use("ggplot")
 
 from prepare_sector_network import co2_emissions_year

scripts/prepare_sector_network.py

@@ -11,6 +11,7 @@ import logging
 import os
 import re
 from itertools import product
+from types import SimpleNamespace
 
 import networkx as nx
 import numpy as np
@@ -22,18 +23,13 @@ from add_electricity import calculate_annuity, sanitize_carriers
 from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2
 from networkx.algorithms import complement
 from networkx.algorithms.connectivity.edge_augmentation import k_edge_augmentation
+from packaging.version import Version, parse
 from pypsa.geo import haversine_pts
 from pypsa.io import import_components_from_dataframe
 from scipy.stats import beta
 
-logger = logging.getLogger(__name__)
-
-from types import SimpleNamespace
-
 spatial = SimpleNamespace()
-
+logger = logging.getLogger(__name__)
-from packaging.version import Version, parse
-
 pd_version = parse(pd.__version__)
 agg_group_kwargs = dict(numeric_only=False) if pd_version >= Version("1.3") else {}
 

scripts/retrieve_sector_databundle.py

@@ -7,14 +7,13 @@ Retrieve and extract data bundle for sector-coupled studies.
 """
 
 import logging
-
-logger = logging.getLogger(__name__)
-
 import tarfile
 from pathlib import Path
 
 from _helpers import configure_logging, progress_retrieve, validate_checksum
 
+logger = logging.getLogger(__name__)
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake

scripts/solve_network.py

@@ -39,10 +39,10 @@ import xarray as xr
 from _benchmark import memory_logger
 from _helpers import configure_logging, get_opt, update_config_with_sector_opts
 from pypsa.descriptors import get_activity_mask
+from pypsa.descriptors import get_switchable_as_dense as get_as_dense
 
 logger = logging.getLogger(__name__)
 pypsa.pf.logger.setLevel(logging.WARNING)
-from pypsa.descriptors import get_switchable_as_dense as get_as_dense
 
 
 def add_land_use_constraint(n, planning_horizons, config):