rm CondaPkg environment

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/boykovkolmogorov.py

@@ -317,7 +317,7 @@ def boykov_kolmogorov_impl(G, s, t, capacity, residual, cutoff):
         v = n
         while v is not None:
             path.append(v)
-            if v == s or v == t:
+            if v in (s, t):
                 base_dist = 0
                 break
             elif timestamp[v] == time:

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/networksimplex.py

@@ -15,7 +15,6 @@ class _DataEssentialsAndFunctions:
     def __init__(
         self, G, multigraph, demand="demand", capacity="capacity", weight="weight"
     ):
-
         # Number all nodes and edges and hereafter reference them using ONLY their numbers
         self.node_list = list(G)  # nodes
         self.node_indices = {u: i for i, u in enumerate(self.node_list)}  # node indices

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/tests/test_maxflow.py

@@ -451,8 +451,8 @@ class TestMaxFlowMinCutInterface:
         G = self.H
         fv = 1.0
         to_test = (
-            (shortest_augmenting_path, dict(two_phase=True)),
-            (preflow_push, dict(global_relabel_freq=5)),
+            (shortest_augmenting_path, {"two_phase": True}),
+            (preflow_push, {"global_relabel_freq": 5}),
         )
         for interface_func in interface_funcs:
             for flow_func, kwargs in to_test:

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/tests/test_maxflow_large_graph.py

@@ -85,7 +85,7 @@ class TestMaxflowLargeGraph:
         G = nx.complete_graph(N)
         nx.set_edge_attributes(G, 5, "capacity")
         R = build_residual_network(G, "capacity")
-        kwargs = dict(residual=R)
+        kwargs = {"residual": R}
 
         for flow_func in flow_funcs:
             kwargs["flow_func"] = flow_func
@@ -98,7 +98,7 @@ class TestMaxflowLargeGraph:
         # N = 100 # this gives a graph with 5051 nodes
         G = gen_pyramid(N)
         R = build_residual_network(G, "capacity")
-        kwargs = dict(residual=R)
+        kwargs = {"residual": R}
 
         for flow_func in flow_funcs:
             kwargs["flow_func"] = flow_func
@@ -111,7 +111,7 @@ class TestMaxflowLargeGraph:
         s = 1
         t = len(G)
         R = build_residual_network(G, "capacity")
-        kwargs = dict(residual=R)
+        kwargs = {"residual": R}
 
         # do one flow_func to save time
         flow_func = flow_funcs[0]
@@ -127,7 +127,7 @@ class TestMaxflowLargeGraph:
         s = 1
         t = len(G)
         R = build_residual_network(G, "capacity")
-        kwargs = dict(residual=R)
+        kwargs = {"residual": R}
 
         for flow_func in flow_funcs:
             validate_flows(G, s, t, 1202018, flow_func(G, s, t, **kwargs), flow_func)
@@ -137,7 +137,7 @@ class TestMaxflowLargeGraph:
         s = 1
         t = len(G)
         R = build_residual_network(G, "capacity")
-        kwargs = dict(residual=R)
+        kwargs = {"residual": R}
 
         # do one flow_func to save time
         flow_func = flow_funcs[0]

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/tests/test_mincost.py

@@ -438,7 +438,7 @@ class TestMinCostFlow:
         pytest.raises(nx.NetworkXNotImplemented, nx.capacity_scaling, G)
         G = nx.DiGraph()
         pytest.raises(nx.NetworkXError, nx.network_simplex, G)
-        pytest.raises(nx.NetworkXError, nx.capacity_scaling, G)
+        # pytest.raises(nx.NetworkXError, nx.capacity_scaling, G)
         G.add_node(0, demand=float("inf"))
         pytest.raises(nx.NetworkXError, nx.network_simplex, G)
         pytest.raises(nx.NetworkXUnfeasible, nx.capacity_scaling, G)

.CondaPkg/env/Lib/site-packages/networkx/algorithms/flow/tests/test_networksimplex.py

@@ -38,8 +38,8 @@ def simple_no_flow_graph():
 def get_flowcost_from_flowdict(G, flowDict):
     """Returns flow cost calculated from flow dictionary"""
     flowCost = 0
-    for u in flowDict.keys():
-        for v in flowDict[u].keys():
+    for u in flowDict:
+        for v in flowDict[u]:
             flowCost += flowDict[u][v] * G[u][v]["weight"]
     return flowCost