remove six dependency (#245)

scripts/_helpers.py

@@ -156,7 +156,6 @@ def aggregate_p_curtailed(n):
     ])
 
 def aggregate_costs(n, flatten=False, opts=None, existing_only=False):
-    from six import iterkeys, itervalues
 
     components = dict(Link=("p_nom", "p0"),
                       Generator=("p_nom", "p"),
@@ -167,8 +166,8 @@ def aggregate_costs(n, flatten=False, opts=None, existing_only=False):
 
     costs = {}
     for c, (p_nom, p_attr) in zip(
-        n.iterate_components(iterkeys(components), skip_empty=False),
-        itervalues(components)
+        n.iterate_components(components.keys(), skip_empty=False),
+        components.values()
     ):
         if c.df.empty: continue
         if not existing_only: p_nom += "_opt"

scripts/base_network.py

@@ -74,7 +74,6 @@ import scipy as sp
 import networkx as nx
 
 from scipy.sparse import csgraph
-from six import iteritems
 from itertools import product
 
 from shapely.geometry import Point, LineString
@@ -268,13 +267,13 @@ def _apply_parameter_corrections(n):
 
     if corrections is None: return
 
-    for component, attrs in iteritems(corrections):
+    for component, attrs in corrections.items():
         df = n.df(component)
         oid = _get_oid(df)
         if attrs is None: continue
 
-        for attr, repls in iteritems(attrs):
-            for i, r in iteritems(repls):
+        for attr, repls in attrs.items():
+            for i, r in repls.items():
                 if i == 'oid':
                     r = oid.map(repls["oid"]).dropna()
                 elif i == 'index':

scripts/build_shapes.py

@@ -73,7 +73,7 @@ from _helpers import configure_logging
 import os
 import numpy as np
 from operator import attrgetter
-from six.moves import reduce
+from functools import reduce
 from itertools import takewhile
 
 import pandas as pd

scripts/cluster_network.py

@@ -135,7 +135,7 @@ import pyomo.environ as po
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-from six.moves import reduce
+from functools import reduce
 
 from pypsa.networkclustering import (busmap_by_kmeans, busmap_by_spectral_clustering,
                                      _make_consense, get_clustering_from_busmap)

scripts/make_summary.py

@@ -60,7 +60,6 @@ import os
 import pypsa
 import pandas as pd
 
-from six import iteritems
 from add_electricity import load_costs, update_transmission_costs
 
 idx = pd.IndexSlice
@@ -386,7 +385,7 @@ def make_summaries(networks_dict, country='all'):
     for output in outputs:
         dfs[output] = pd.DataFrame(columns=columns,dtype=float)
 
-    for label, filename in iteritems(networks_dict):
+    for label, filename in networks_dict.items():
         print(label, filename)
         if not os.path.exists(filename):
             print("does not exist!!")
@@ -417,7 +416,7 @@ def make_summaries(networks_dict, country='all'):
 def to_csv(dfs):
     dir = snakemake.output[0]
     os.makedirs(dir, exist_ok=True)
-    for key, df in iteritems(dfs):
+    for key, df in dfs.items():
         df.to_csv(os.path.join(dir, f"{key}.csv"))
 
 

scripts/plot_network.py

@@ -25,7 +25,6 @@ from _helpers import (load_network_for_plots, aggregate_p, aggregate_costs,
 
 import pandas as pd
 import numpy as np
-from six.moves import zip
 
 import cartopy.crs as ccrs
 import matplotlib.pyplot as plt

scripts/prepare_network.py

@@ -62,7 +62,6 @@ import re
 import pypsa
 import numpy as np
 import pandas as pd
-from six import iteritems
 
 from add_electricity import load_costs, update_transmission_costs
 
@@ -145,7 +144,7 @@ def average_every_nhours(n, offset):
 
     for c in n.iterate_components():
         pnl = getattr(m, c.list_name+"_t")
-        for k, df in iteritems(c.pnl):
+        for k, df in c.pnl.items():
             if not df.empty:
                 pnl[k] = df.resample(offset).mean()
 

scripts/simplify_network.py

@@ -93,8 +93,7 @@ import numpy as np
 import scipy as sp
 from scipy.sparse.csgraph import connected_components, dijkstra
 
-from six import iteritems
-from six.moves import reduce
+from functools import reduce
 
 import pypsa
 from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
@@ -193,7 +192,7 @@ def _aggregate_and_move_components(n, busmap, connection_costs_to_bus, aggregate
         n.mremove(c, n.df(c).index)
 
         import_components_from_dataframe(n, df, c)
-        for attr, df in iteritems(pnl):
+        for attr, df in pnl.items():
             if not df.empty:
                 import_series_from_dataframe(n, df, c, attr)
 
@@ -237,7 +236,7 @@ def simplify_links(n):
                       if len(G.adj[m]) > 2 or (set(G.adj[m]) - nodes)}
 
         for u in supernodes:
-            for m, ls in iteritems(G.adj[u]):
+            for m, ls in G.adj[u].items():
                 if m not in nodes or m in seen: continue
 
                 buses = [u, m]
@@ -245,7 +244,7 @@ def simplify_links(n):
 
                 while m not in (supernodes | seen):
                     seen.add(m)
-                    for m2, ls in iteritems(G.adj[m]):
+                    for m2, ls in G.adj[m].items():
                         if m2 in seen or m2 == u: continue
                         buses.append(m2)
                         links.append(list(ls)) # [name for name in ls])