update version compatibility handling

rules/postprocess.smk

@@ -45,7 +45,7 @@ if config["foresight"] != "perfect":
             (
                 LOGS
                 + "plot_power_network/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.log"
-            )
+            ),
         benchmark:
             (
                 BENCHMARKS
@@ -74,7 +74,7 @@ if config["foresight"] != "perfect":
             (
                 LOGS
                 + "plot_hydrogen_network/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.log"
-            )
+            ),
         benchmark:
             (
                 BENCHMARKS
@@ -102,7 +102,7 @@ if config["foresight"] != "perfect":
             (
                 LOGS
                 + "plot_gas_network/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.log"
-            )
+            ),
         benchmark:
             (
                 BENCHMARKS

scripts/_helpers.py

@@ -264,7 +264,6 @@ def mock_snakemake(
     import os
 
     import snakemake as sm
-    from packaging.version import Version, parse
     from pypsa.descriptors import Dict
     from snakemake.script import Snakemake
 
@@ -290,13 +289,12 @@ def mock_snakemake(
             if os.path.exists(p):
                 snakefile = p
                 break
-        kwargs = (
-            dict(rerun_triggers=[]) if parse(sm.__version__) > Version("7.7.0") else {}
-        )
         if isinstance(configfiles, str):
             configfiles = [configfiles]
 
-        workflow = sm.Workflow(snakefile, overwrite_configfiles=configfiles, **kwargs)
+        workflow = sm.Workflow(
+            snakefile, overwrite_configfiles=configfiles, rerun_triggers=[]
+        )
         workflow.include(snakefile)
 
         if configfiles:

scripts/base_network.py

@@ -78,10 +78,13 @@ import shapely.prepared
 import shapely.wkt
 import yaml
 from _helpers import configure_logging
+from packaging.version import Version, parse
 from scipy import spatial
 from scipy.sparse import csgraph
 from shapely.geometry import LineString, Point
 
+PD_GE_2_2 = parse(pd.__version__) >= Version("2.2")
+
 logger = logging.getLogger(__name__)
 
 
@@ -524,12 +527,13 @@ def _set_countries_and_substations(n, config, country_shapes, offshore_shapes):
         )
         return pd.Series(key, index)
 
+    compat_kws = dict(include_groups=False) if PD_GE_2_2 else {}
     gb = buses.loc[substation_b].groupby(
         ["x", "y"], as_index=False, group_keys=False, sort=False
     )
-    bus_map_low = gb.apply(prefer_voltage, "min", include_groups=False)
+    bus_map_low = gb.apply(prefer_voltage, "min", **compat_kws)
     lv_b = (bus_map_low == bus_map_low.index).reindex(buses.index, fill_value=False)
-    bus_map_high = gb.apply(prefer_voltage, "max", include_groups=False)
+    bus_map_high = gb.apply(prefer_voltage, "max", **compat_kws)
     hv_b = (bus_map_high == bus_map_high.index).reindex(buses.index, fill_value=False)
 
     onshore_b = pd.Series(False, buses.index)

scripts/build_industrial_distribution_key.py

@@ -13,7 +13,6 @@ from itertools import product
 import country_converter as coco
 import geopandas as gpd
 import pandas as pd
-from packaging.version import Version, parse
 
 logger = logging.getLogger(__name__)
 cc = coco.CountryConverter()
@@ -84,12 +83,7 @@ def prepare_hotmaps_database(regions):
 
     gdf = gpd.GeoDataFrame(df, geometry="coordinates", crs="EPSG:4326")
 
-    kws = (
+    gdf = gpd.sjoin(gdf, regions, how="inner", predicate="within")
-        dict(op="within")
-        if parse(gpd.__version__) < Version("0.10")
-        else dict(predicate="within")
-    )
-    gdf = gpd.sjoin(gdf, regions, how="inner", **kws)
 
     gdf.rename(columns={"index_right": "bus"}, inplace=True)
     gdf["country"] = gdf.bus.str[:2]

scripts/cluster_gas_network.py

@@ -10,7 +10,6 @@ import logging
 
 import geopandas as gpd
 import pandas as pd
-from packaging.version import Version, parse
 from pypsa.geo import haversine_pts
 from shapely import wkt
 
@@ -41,12 +40,9 @@ def build_clustered_gas_network(df, bus_regions, length_factor=1.25):
     for i in [0, 1]:
         gdf = gpd.GeoDataFrame(geometry=df[f"point{i}"], crs="EPSG:4326")
 
-        kws = (
+        bus_mapping = gpd.sjoin(
-            dict(op="within")
+            gdf, bus_regions, how="left", predicate="within"
-            if parse(gpd.__version__) < Version("0.10")
+        ).index_right
-            else dict(predicate="within")
-        )
-        bus_mapping = gpd.sjoin(gdf, bus_regions, how="left", **kws).index_right
         bus_mapping = bus_mapping.groupby(bus_mapping.index).first()
 
         df[f"bus{i}"] = bus_mapping

scripts/cluster_network.py

@@ -135,6 +135,7 @@ import pypsa
 import seaborn as sns
 from _helpers import configure_logging, update_p_nom_max
 from add_electricity import load_costs
+from packaging.version import Version, parse
 from pypsa.clustering.spatial import (
     busmap_by_greedy_modularity,
     busmap_by_hac,
@@ -142,6 +143,8 @@ from pypsa.clustering.spatial import (
     get_clustering_from_busmap,
 )
 
+PD_GE_2_2 = parse(pd.__version__) >= Version("2.2")
+
 warnings.filterwarnings(action="ignore", category=UserWarning)
 idx = pd.IndexSlice
 logger = logging.getLogger(__name__)
@@ -362,9 +365,11 @@ def busmap_for_n_clusters(
                 f"`algorithm` must be one of 'kmeans' or 'hac'. Is {algorithm}."
             )
 
+    compat_kws = dict(include_groups=False) if PD_GE_2_2 else {}
+
     return (
         n.buses.groupby(["country", "sub_network"], group_keys=False)
-        .apply(busmap_for_country, include_groups=False)
+        .apply(busmap_for_country, **compat_kws)
         .squeeze()
         .rename("busmap")
     )

scripts/prepare_sector_network.py

@@ -23,15 +23,12 @@ from add_electricity import calculate_annuity, sanitize_carriers, sanitize_locat
 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
 
 spatial = SimpleNamespace()
 logger = logging.getLogger(__name__)
-pd_version = parse(pd.__version__)
-agg_group_kwargs = dict(numeric_only=False) if pd_version >= Version("1.3") else {}
 
 
 def define_spatial(nodes, options):
@@ -1853,16 +1850,7 @@ def add_heat(n, costs):
                 p_nom_extendable=True,
             )
 
-            if isinstance(options["tes_tau"], dict):
             tes_time_constant_days = options["tes_tau"][name_type]
-            else:
-                logger.warning(
-                    "Deprecated: a future version will require you to specify 'tes_tau' ",
-                    "for 'decentral' and 'central' separately.",
-                )
-                tes_time_constant_days = (
-                    options["tes_tau"] if name_type == "decentral" else 180.0
-                )
 
             n.madd(
                 "Store",
@@ -3404,7 +3392,7 @@ def cluster_heat_buses(n):
         # cluster heat nodes
         # static dataframe
         agg = define_clustering(df.columns, aggregate_dict)
-        df = df.groupby(level=0).agg(agg, **agg_group_kwargs)
+        df = df.groupby(level=0).agg(agg, numeric_only=False)
         # time-varying data
         pnl = c.pnl
         agg = define_clustering(pd.Index(pnl.keys()), aggregate_dict)
@@ -3413,7 +3401,7 @@ def cluster_heat_buses(n):
             def renamer(s):
                 return s.replace("residential ", "").replace("services ", "")
 
-            pnl[k] = pnl[k].T.groupby(renamer).agg(agg[k], **agg_group_kwargs).T
+            pnl[k] = pnl[k].T.groupby(renamer).agg(agg[k], numeric_only=False).T
 
         # remove unclustered assets of service/residential
         to_drop = c.df.index.difference(df.index)