Remove unnecessary list coercions.

Author: darius

csp.py

@@ -658,7 +658,7 @@ def solve_zebra(algorithm=min_conflicts, **args):
     ans = algorithm(z, **args)
     for h in range(1, 6):
         print('House', h, end=' ')
-        for (var, val) in list(ans.items()):
+        for (var, val) in ans.items():
             if val == h:
                 print(var, end=' ')
         print()

learning.py

@@ -209,8 +209,7 @@ def __getitem__(self, item):
 
     def top(self, n):
         "Return (count, obs) tuples for the n most frequent observations."
-        return heapq.nlargest(
-            n, [(v, k) for (k, v) in list(self.dictionary.items())])
+        return heapq.nlargest(n, [(v, k) for (k, v) in self.dictionary.items()])
 
     def sample(self):
         "Return a random sample from the distribution."
@@ -301,7 +300,7 @@ def add(self, val, subtree):
     def display(self, indent=0):
         name = self.attrname
         print('Test', name)
-        for (val, subtree) in list(self.branches.items()):
+        for (val, subtree) in self.branches.items():
             print(' ' * 4 * indent, name, '=', val, '==>', end=' ')
             subtree.display(indent + 1)
 
@@ -885,7 +884,7 @@ def RestaurantDataSet(examples=None):
 def T(attrname, branches):
     branches = dict((value, (child if isinstance(child, DecisionFork)
                              else DecisionLeaf(child)))
-                    for value, child in list(branches.items()))
+                    for value, child in branches.items())
     return DecisionFork(restaurant.attrnum(attrname), attrname, branches)
 
 """ [Figure 18.2]

mdp.py

@@ -94,7 +94,7 @@ def to_arrows(self, policy):
         chars = {
             (1, 0): '>', (0, 1): '^', (-1, 0): '<', (0, -1): 'v', None: '.'}
         return self.to_grid(
-                dict([(s, chars[a]) for (s, a) in list(policy.items())]))
+                dict([(s, chars[a]) for (s, a) in policy.items()]))
 
 # ______________________________________________________________________________
 """ [Figure 17.1]

nlp.py

@@ -14,7 +14,7 @@ def Rules(**rules):
     >>> Rules(A = "B C | D E")
     {'A': [['B', 'C'], ['D', 'E']]}
     """
-    for (lhs, rhs) in list(rules.items()):
+    for (lhs, rhs) in rules.items():
         rules[lhs] = [alt.strip().split() for alt in rhs.split('|')]
     return rules
 
@@ -24,7 +24,7 @@ def Lexicon(**rules):
     >>> Lexicon(Art = "the | a | an")
     {'Art': ['the', 'a', 'an']}
     """
-    for (lhs, rhs) in list(rules.items()):
+    for (lhs, rhs) in rules.items():
         rules[lhs] = [word.strip() for word in rhs.split('|')]
     return rules
 

probability.py

@@ -46,7 +46,7 @@ def __init__(self, varname='?', freqs=None):
         self.varname = varname
         self.values = []
         if freqs:
-            for (v, p) in list(freqs.items()):
+            for (v, p) in freqs.items():
                 self[v] = p
             self.normalize()
 
@@ -237,10 +237,10 @@ def __init__(self, X, parents, cpt):
         elif isinstance(cpt, dict):
             # one parent, 1-tuple
             if cpt and isinstance(list(cpt.keys())[0], bool):
-                cpt = dict(((v,), p) for v, p in list(cpt.items()))
+                cpt = dict(((v,), p) for v, p in cpt.items())
 
         assert isinstance(cpt, dict)
-        for vs, p in list(cpt.items()):
+        for vs, p in cpt.items():
             assert isinstance(vs, tuple) and len(vs) == len(parents)
             assert all(isinstance(v, bool) for v in vs)
             assert 0 <= p <= 1
@@ -390,7 +390,7 @@ def normalize(self):
         "Return my probabilities; must be down to one variable."
         assert len(self.variables) == 1
         return ProbDist(self.variables[0],
-                        dict((k, v) for ((k,), v) in list(self.cpt.items())))
+                        dict((k, v) for ((k,), v) in self.cpt.items()))
 
     def p(self, e):
         "Look up my value tabulated for e."
@@ -454,7 +454,7 @@ def rejection_sampling(X, e, bn, N):
 def consistent_with(event, evidence):
     "Is event consistent with the given evidence?"
     return all(evidence.get(k, v) == v
-               for k, v in list(event.items()))
+               for k, v in event.items())
 
 # _________________________________________________________________________
 

search.py

@@ -639,7 +639,7 @@ def __init__(self, dict=None, directed=True):
     def make_undirected(self):
         "Make a digraph into an undirected graph by adding symmetric edges."
         for a in list(self.dict.keys()):
-            for (b, distance) in list(self.dict[a].items()):
+            for (b, distance) in self.dict[a].items():
                 self.connect1(b, a, distance)
 
     def connect(self, A, B, distance=1):