Iteritems no longer

src/sage/combinat/designs/orthogonal_arrays_find_recursive.pyx

@@ -799,7 +799,7 @@ cpdef find_brouwer_separable_design(int k, int n):
 from sage.combinat.designs.database import QDM as __QDM
 cdef dict _QDM = __QDM
 cdef dict ioa_indexed_by_n_minus_x = {}
-for x in _QDM.itervalues():
+for x in _QDM.values():
     for (n, _, _, u), (k, _) in x.items():
         if u > 1:
             if n not in ioa_indexed_by_n_minus_x:

src/sage/graphs/base/boost_graph.pyx

@@ -273,7 +273,7 @@ cdef boost_clustering_coeff(BoostGenGraph *g, vertices):
             result_d = g[0].clustering_coeff(vi)
             sig_off()
             clust_of_v[v] = result_d
-        return ((sum(clust_of_v.itervalues()) / len(clust_of_v)), clust_of_v)
+        return ((sum(clust_of_v.values()) / len(clust_of_v)), clust_of_v)
 
 
 cpdef clustering_coeff(g, vertices=None):

src/sage/groups/perm_gps/partn_ref/refinement_graphs.pyx

@@ -1054,7 +1054,7 @@ def get_orbits(list gens, int n):
     OP_dealloc(OP)
     sig_free(perm_ints)
 
-    return list(orbit_dict.itervalues())
+    return list(orbit_dict.values())
 
 
 # Canonical augmentation

src/sage/libs/gap/element.pyx

@@ -193,12 +193,13 @@ cdef Obj make_gap_record(sage_dict) except NULL:
         sage: libgap({'a': 1, 'b':123})   # indirect doctest
         rec( a := 1, b := 123 )
     """
-    data = [ (str(key), libgap(value)) for key, value in sage_dict.iteritems() ]
-
+    cdef list data
     cdef Obj rec
     cdef GapElement val
     cdef UInt rnam
 
+    data = [(str(key), libgap(value)) for key, value in sage_dict.items()]
+
     try:
         GAP_Enter()
         rec = GAP_NewPrecord(len(data))

src/sage/libs/singular/option.pyx

@@ -166,7 +166,7 @@ cdef class LibSingularOptions_abstract:
             sage: opt['degBound']
             2
         """
-        for k,v in kwds.iteritems():
+        for k, v in kwds.items():
             self[k] = v
 
     def __getitem__(self, name):
@@ -615,7 +615,7 @@ cdef class LibSingularOptionsContext:
         self.bck_degBound.append(Kstd1_deg)
         self.bck_multBound.append(Kstd1_mu)
         opt = self.opt.__class__()
-        for k,v in self.options.iteritems():
+        for k, v in self.options.items():
             opt[k] = v
 
     def __call__(self, **kwds):
@@ -631,8 +631,7 @@ cdef class LibSingularOptionsContext:
             ....:   opt['redTail']
             False
         """
-        new = self.__class__(self.opt, **kwds)
-        return new
+        return self.__class__(self.opt, **kwds)
 
     def __exit__(self, typ, value, tb):
         """

src/sage/matrix/matrix2.pyx

@@ -3018,7 +3018,7 @@ cdef class Matrix(Matrix1):
                 return self.dense_matrix()
 
         if self.is_sparse():
-            values = {ij: phi(v) for ij, v in self.dict().iteritems()}
+            values = {ij: phi(v) for ij, v in self.dict().items()}
             if R is None:
                 R = sage.structure.sequence.Sequence(values.values()).universe()
         else:

src/sage/matrix/matrix_sparse.pyx

@@ -156,7 +156,7 @@ cdef class Matrix_sparse(matrix.Matrix):
 
         cdef long h = 0, k, l
         cdef Py_ssize_t i, j
-        for ij, x in D.iteritems():
+        for ij, x in D.items():
             sig_check()
             i = (<tuple>ij)[0]
             j = (<tuple>ij)[1]
@@ -362,7 +362,7 @@ cdef class Matrix_sparse(matrix.Matrix):
     def _unpickle_generic(self, data, int version):
         cdef Py_ssize_t i, j
         if version == -1:
-            for (i, j), x in data.iteritems():
+            for (i, j), x in data.items():
                 self.set_unsafe(i, j, x)
         else:
             raise RuntimeError("unknown matrix version (=%s)" % version)
@@ -643,7 +643,7 @@ cdef class Matrix_sparse(matrix.Matrix):
         R = phi.codomain()
         M = sage.matrix.matrix_space.MatrixSpace(R, self._nrows,
                                                  self._ncols, sparse=True)
-        return M({ij: phi(z) for ij, z in self.dict().iteritems()})
+        return M({ij: phi(z) for ij, z in self.dict().items()})
 
     def apply_map(self, phi, R=None, sparse=True):
         r"""
@@ -768,7 +768,7 @@ cdef class Matrix_sparse(matrix.Matrix):
             zero_res = phi(self.base_ring()(0))
         else:
             zero_res = None
-        v = [(ij, phi(z)) for ij,z in self_dict.iteritems()]
+        v = [(ij, phi(z)) for ij,z in self_dict.items()]
         if R is None:
             w = [x for _, x in v]
             if zero_res is not None:
@@ -826,7 +826,8 @@ cdef class Matrix_sparse(matrix.Matrix):
 
         if self._nrows==0 or self._ncols==0:
             return self.__copy__()
-        v = [(ij, sage.calculus.functional.derivative(z, var)) for ij, z in self.dict().iteritems()]
+        v = [(ij, sage.calculus.functional.derivative(z, var))
+             for ij, z in self.dict().items()]
         if R is None:
             w = [x for _, x in v]
             w = sage.structure.sequence.Sequence(w)
@@ -1154,7 +1155,7 @@ cdef class Matrix_sparse(matrix.Matrix):
             raise ArithmeticError("number of rows of matrix must equal degree of vector")
         parent = self.row_ambient_module(base_ring=None, sparse=v.is_sparse_c())
         s = parent.zero_vector()
-        for (i, j), a in self._dict().iteritems():
+        for (i, j), a in self._dict().items():
             s[j] += v[i] * a
         return s
 
@@ -1207,7 +1208,7 @@ cdef class Matrix_sparse(matrix.Matrix):
             raise ArithmeticError("number of columns of matrix must equal degree of vector")
         parent = self.column_ambient_module(base_ring=None, sparse=v.is_sparse_c())
         s = parent.zero_vector()
-        for (i, j), a in self._dict().iteritems():
+        for (i, j), a in self._dict().items():
             s[i] += a * v[j]
         return s
 

src/sage/matrix/matrix_symbolic_dense.pyx

@@ -977,7 +977,7 @@ cdef class Matrix_symbolic_dense(Matrix_generic_dense):
 
         if args:
             if len(args) == 1 and isinstance(args[0], dict):
-                kwargs = {repr(x): vx for x, vx in args[0].iteritems()}
+                kwargs = {repr(x): vx for x, vx in args[0].items()}
             else:
                 raise ValueError('use named arguments, like EXPR(x=..., y=...)')
 

src/sage/matrix/matrix_symbolic_sparse.pyx

@@ -985,7 +985,7 @@ cdef class Matrix_symbolic_sparse(Matrix_generic_sparse):
 
         if args:
             if len(args) == 1 and isinstance(args[0], dict):
-                kwargs = {repr(x): vx for x, vx in args[0].iteritems()}
+                kwargs = {repr(x): vx for x, vx in args[0].items()}
             else:
                 raise ValueError('use named arguments, like EXPR(x=..., y=...)')
 

src/sage/matroids/linear_matroid.pyx

@@ -2200,14 +2200,14 @@ cdef class LinearMatroid(BasisExchangeMatroid):
                         while todo:
                             r = todo.pop()
                             cocirc = self.fundamental_cocycle(B, r)
-                            for s, v in cocirc.iteritems():
+                            for s, v in cocirc.items():
                                 if s != r and s not in mult2:
                                     mult2[s] = mult[r] * v
                                     todo2.add(s)
                         while todo2:
                             s = todo2.pop()
                             circ = self.fundamental_cycle(B, s)
-                            for t, w in circ.iteritems():
+                            for t, w in circ.items():
                                 if t != s and t not in mult:
                                     mult[t] = mult2[s] / w
                                     if t not in T:
@@ -2398,7 +2398,7 @@ cdef class LinearMatroid(BasisExchangeMatroid):
                         parallel = True
                         e = min(p)
                         ratio = c[e] / p[e]
-                        for f, w in p.iteritems():
+                        for f, w in p.items():
                             if c[f] / w != ratio:
                                 parallel = False
                                 break

src/sage/matroids/matroid.pyx

@@ -6160,7 +6160,7 @@ cdef class Matroid(SageObject):
         if not G.is_connected():
             return False
         # Step 4: Apply algorithm recursively
-        for B, M in Y_components.iteritems():
+        for B, M in Y_components.items():
             N = M.simplify()
             new_basis = basis & (B | Y)
             # the set of fundamental cocircuit that might be separating for N
@@ -7672,7 +7672,7 @@ cdef class Matroid(SageObject):
             dist += 1
             X3 = X2.intersection(w)
 
-        for x, y in layers.iteritems():
+        for x, y in layers.items():
             for z in y:
                 d[z] = x
         if not X3:                 # if no path from X1 to X2, then no augmenting set exists

src/sage/matroids/union_matroid.pyx

@@ -226,7 +226,7 @@ cdef class MatroidSum(Matroid):
                 partition[i] = set()
             partition[i].add(x)
         r = 0
-        for (i, Xi) in partition.iteritems():
+        for i, Xi in partition.items():
             r += self.summands[i]._rank(frozenset(Xi))
         return r
 

src/sage/misc/reset.pyx

@@ -147,7 +147,7 @@ def restore(vars=None):
 
 def _restore(G, D, vars):
     if vars is None:
-        for k, v in D.iteritems():
+        for k, v in D.items():
             G[k] = v
     else:
         if isinstance(vars, str):

src/sage/misc/weak_dict.pyx

@@ -813,24 +813,6 @@ cdef class WeakValueDictionary(dict):
         """
         return list(iter(self))
 
-    def itervalues(self):
-        """
-        Deprecated.
-
-        EXAMPLES::
-
-            sage: import sage.misc.weak_dict
-            sage: class Vals(): pass
-            sage: L = [Vals() for _ in range(10)]
-            sage: D = sage.misc.weak_dict.WeakValueDictionary(enumerate(L))
-            sage: T = list(D.itervalues())
-            doctest:warning...:
-            DeprecationWarning: use values instead
-            See https://github.com/sagemath/sage/issues/34488 for details.
-        """
-        deprecation(34488, "use values instead")
-        return self.values()
-
     def values(self):
         """
         Iterate over the values of this dictionary.
@@ -918,22 +900,6 @@ cdef class WeakValueDictionary(dict):
         """
         return list(self.values())
 
-    def iteritems(self):
-        """
-        EXAMPLES::
-
-            sage: import sage.misc.weak_dict
-            sage: class Vals(): pass
-            sage: L = [Vals() for _ in range(10)]
-            sage: D = sage.misc.weak_dict.WeakValueDictionary(enumerate(L))
-            sage: T = list(D.iteritems())
-            doctest:warning...:
-            DeprecationWarning: use items instead
-            See https://github.com/sagemath/sage/issues/34488 for details.
-        """
-        deprecation(34488, "use items instead")
-        return self.items()
-
     def items(self):
         """
         Iterate over the items of this dictionary.

src/sage/numerical/backends/cvxopt_backend.pyx

@@ -534,7 +534,7 @@ cdef class CVXOPTBackend(GenericBackend):
 
         G = matrix(G)
 
-        #cvxopt minimizes on default
+        # cvxopt minimizes on default
         if self.is_maximize:
             c = [-1 * float(e) for e in self.objective_function]
         else:
@@ -544,12 +544,12 @@ cdef class CVXOPTBackend(GenericBackend):
         h = [float(e) for e in h]
         h = matrix(h)
 
-        #solvers comes from the cvxopt library
-        for k,v in self.param.iteritems():
+        # solvers comes from the cvxopt library
+        for k, v in self.param.items():
             solvers.options[k] = v
-        self.answer = solvers.lp(c,G,h)
+        self.answer = solvers.lp(c, G, h)
 
-        #possible outcomes
+        # possible outcomes
         if self.answer['status'] == 'optimized':
             pass
         elif self.answer['status'] == 'primal infeasible':

src/sage/numerical/backends/cvxopt_sdp_backend.pyx

@@ -138,15 +138,15 @@ cdef class CVXOPTSDPBackend(MatrixSDPBackend):
                     G_temp.insert(j,[float(0) for t in range(self.matrices_dim[row_index]**2)])
             G_matrix += [c_matrix(G_temp)]
             debug_g += [(G_temp)]
-        #raise Exception("G_matrix " + str(debug_g) + "\nh_matrix: " + str(debug_h) + "\nc_matrix: " + str(debug_c))
+        # raise Exception("G_matrix " + str(debug_g) + "\nh_matrix: " + str(debug_h) + "\nc_matrix: " + str(debug_c))
 
-        #solvers comes from the cvxopt library
-        for k,v in self.param.iteritems():
+        # solvers comes from the cvxopt library
+        for k, v in self.param.items():
             solvers.options[k] = v
 
         self.answer = solvers.sdp(c,Gs=G_matrix,hs=h_matrix)
 
-        #possible outcomes
+        # possible outcomes
         if self.answer['status'] == 'optimized':
             pass
         elif self.answer['status'] == 'primal infeasible':

src/sage/numerical/backends/scip_backend.pyx

@@ -263,11 +263,11 @@ cdef class SCIPBackend(GenericBackend):
             self.model.freeTransform()
         if coeff is None:
             return self.variables[variable].getObj()
-        else:
-            objexpr = self.model.getObjective()
-            var = self.variables[variable]
-            linfun = sum([e * c for e, c in objexpr.terms.iteritems() if e != var]) + var * coeff
-            self.model.setObjective(linfun, sense=self.model.getObjectiveSense())
+
+        objexpr = self.model.getObjective()
+        var = self.variables[variable]
+        linfun = sum([e * c for e, c in objexpr.terms.items() if e != var]) + var * coeff
+        self.model.setObjective(linfun, sense=self.model.getObjectiveSense())
 
     cpdef problem_name(self, name=None):
         """
@@ -500,7 +500,7 @@ cdef class SCIPBackend(GenericBackend):
         valslinear = self.model.getValsLinear(self.get_constraints()[index])
         cdef list indices = []
         cdef list values = []
-        for var, coeff in valslinear.iteritems():
+        for var, coeff in valslinear.items():
             indices.append(namedvars.index(var))
             values.append(coeff)
         return (indices, values)

src/sage/numerical/linear_functions.pxd

@@ -14,7 +14,7 @@ cdef class LinearFunctionsParent_class(Parent):
 cdef class LinearFunction(LinearFunctionOrConstraint):
     cdef dict _f
     cpdef _add_(self, other)
-    cpdef iteritems(self)
+    cpdef items(self)
     cpdef _acted_upon_(self, x, bint self_on_left)
     cpdef is_zero(self)
     cpdef equals(LinearFunction left, LinearFunction right)