a few details in combinat, as suggested by ruff

Author: fchapoton

src/sage/combinat/bijectionist.py

@@ -1671,7 +1671,7 @@ def different_values(p1, p2):
         def merge_until_split():
             for tZ in list(multiple_preimages):
                 tP = multiple_preimages[tZ]
-                for i2 in range(len(tP)-1, -1, -1):
+                for i2 in range(len(tP) - 1, -1, -1):
                     for i1 in range(i2):
                         try:
                             solution = different_values(tP[i1], tP[i2])
@@ -1766,17 +1766,16 @@ def possible_values(self, p=None, optimal=False):
             {'a': {0, 1}, 'b': {0, 1}}
             sage: bij.possible_values(p="a", optimal=True)
             {'a': set(), 'b': set()}
-
         """
         # convert input to set of block representatives
         blocks = set()
         if p in self._A:
             blocks.add(self._P.find(p))
-        elif type(p) is list:  # TODO: this looks very brittle
+        elif isinstance(p, list):  # TODO: this looks very brittle
             for p1 in p:
                 if p1 in self._A:
                     blocks.add(self._P.find(p1))
-                elif type(p1) is list:
+                elif isinstance(p1, list):
                     for p2 in p1:
                         blocks.add(self._P.find(p2))
 
@@ -2083,7 +2082,7 @@ def minimal_subdistributions_blocks_iterator(self):
         minimal_subdistribution.add_constraint(sum(D[p] for p in P) >= 1)
         for p in P:
             minimal_subdistribution.add_constraint(D[p] <= len(self._P.root_to_elements_dict()[p]))
-            minimal_subdistribution.add_constraint(X[p]*len(self._P.root_to_elements_dict()[p]) >= D[p] >= X[p])
+            minimal_subdistribution.add_constraint(X[p] * len(self._P.root_to_elements_dict()[p]) >= D[p] >= X[p])
 
         def add_counter_example_constraint(s):
             for v in self._Z:
@@ -2175,7 +2174,7 @@ def _preprocess_intertwining_relations(self):
         P = self._P
         images = defaultdict(set)  # A^k -> A, a_1,...,a_k +-> {pi(a_1,...,a_k) for all pi}
         for pi_rho in self._pi_rho:
-            for a_tuple in itertools.product(*([A]*pi_rho.numargs)):
+            for a_tuple in itertools.product(*([A] * pi_rho.numargs)):
                 if pi_rho.domain is not None and not pi_rho.domain(*a_tuple):
                     continue
                 a = pi_rho.pi(*a_tuple)
@@ -2565,9 +2564,9 @@ def show(self, variables=True):
                 varid_name[i] = default_name
         for i, (lb, (indices, values), ub) in enumerate(self.milp.constraints()):
             if b.row_name(i):
-                print("    "+b.row_name(i)+":", end=" ")
+                print("    " + b.row_name(i) + ":", end=" ")
             if lb is not None:
-                print(str(ZZ(lb))+" <=", end=" ")
+                print(str(ZZ(lb)) + " <=", end=" ")
             first = True
             for j, c in sorted(zip(indices, values)):
                 c = ZZ(c)
@@ -2581,7 +2580,7 @@ def show(self, variables=True):
                        + varid_name[j]), end=" ")
                 first = False
             # Upper bound
-            print("<= "+str(ZZ(ub)) if ub is not None else "")
+            print("<= " + str(ZZ(ub)) if ub is not None else "")
 
         if variables:
             print("Variables are:")
@@ -2863,8 +2862,8 @@ def add_distribution_constraints(self):
         Z_dict = {z: i for i, z in enumerate(Z)}
         zero = self.milp.linear_functions_parent().zero()
         for tA, tZ in self._bijectionist._elements_distributions:
-            tA_sum = [zero]*len(Z_dict)
-            tZ_sum = [zero]*len(Z_dict)
+            tA_sum = [zero] * len(Z_dict)
+            tZ_sum = [zero] * len(Z_dict)
             for a in tA:
                 p = self._bijectionist._P.find(a)
                 for z in self._bijectionist._possible_block_values[p]:
@@ -3045,12 +3044,13 @@ def add_homomesic_constraints(self):
         tZ = self._bijectionist._possible_block_values
 
         def sum_q(q):
-            return sum(sum(z*self._x[P.find(a), z] for z in tZ[P.find(a)])
+            return sum(sum(z * self._x[P.find(a), z] for z in tZ[P.find(a)])
                        for a in q)
         q0 = Q[0]
         v0 = sum_q(q0)
         for q in Q[1:]:
-            self.milp.add_constraint(len(q0)*sum_q(q) == len(q)*v0, name=f"h: ({q})~({q0})")
+            self.milp.add_constraint(len(q0) * sum_q(q) == len(q) * v0,
+                                     name=f"h: ({q})~({q0})")
 
 
 def _invert_dict(d):

src/sage/combinat/binary_recurrence_sequences.py

@@ -692,7 +692,7 @@ def pthpowers(self, p, Bound):
                             #gather congruence data for the sequence mod ell, which will be mod period(ell) = modu
                             cong1, modu = _find_cong1(p, self, ell)
 
-                            CongNew = []        #makes a new list from cong that is now mod M = lcm(M1, modu) instead of M1
+                            CongNew = []        # makes a new list from cong that is now mod M = lcm(M1, modu) instead of M1
                             M = lcm(M1, modu)
                             for k in range(M // M1):
                                 for i in cong:
@@ -701,18 +701,18 @@ def pthpowers(self, p, Bound):
 
                             M1 = M
 
-                            killed_something = False        #keeps track of when cong1 can rule out a congruence in cong
+                            killed_something = False        # keeps track of when cong1 can rule out a congruence in cong
 
-                            #CRT by hand to gain speed
+                            # CRT by hand to gain speed
                             for i in list(cong):
-                                if not (i % modu in cong1):        #congruence in cong is inconsistent with any in cong1
-                                    cong.remove(i)            #remove that congruence
+                                if (i % modu) not in cong1:        # congruence in cong is inconsistent with any in cong1
+                                    cong.remove(i)            # remove that congruence
                                     killed_something = True
 
                             if M1 == M2:
                                 if not killed_something:
                                     tries += 1
-                                    if tries == 2:            #try twice to rule out congruences
+                                    if tries == 2:            # try twice to rule out congruences
                                         cong = list(cong)
                                         qqold = qq
                                         qq = next_prime_power(qq)

src/sage/combinat/cluster_algebra_quiver/cluster_seed.py

@@ -4345,7 +4345,7 @@ def oriented_exchange_graph(self):
                     j = i.mutate(k, inplace=False)
                     Varj = tuple(sorted(j.cluster()))
                     covers.append((Vari, Varj))
-                    if not(Varj in known_clusters):
+                    if Varj not in known_clusters:
                         known_clusters += [Varj]
                         stack.append(j)
 

src/sage/combinat/composition_tableau.py

@@ -95,7 +95,7 @@ def __init__(self, parent, t):
         if not all(isinstance(row, list) for row in t):
             raise ValueError("a composition tableau must be a list of lists")
 
-        if not [len(r) for r in t] in Compositions():
+        if any(not r for r in t):
             raise ValueError("a composition tableau must be a list of non-empty lists")
 
         # Verify rows weakly decrease from left to right

src/sage/combinat/crystals/crystals.py

@@ -245,7 +245,7 @@ def _rec(self, x, state):
             for j in self._index_set:
                 if j == i:
                     break
-                if not y.e(j) is None:
+                if y.e(j) is not None:
                     hasParent = True
                     break
             if hasParent:

src/sage/combinat/e_one_star.py

@@ -1418,7 +1418,7 @@ def __init__(self, sigma, method='suffix'):
             raise ValueError("the substitution (%s) must be unimodular" % sigma)
 
         first_letter = sigma.codomain().alphabet()[0]
-        if not (first_letter in ZZ) or (first_letter < 1):
+        if first_letter not in ZZ or first_letter < 1:
             raise ValueError("the substitution (%s) must be defined on positive integers" % sigma)
 
         self._sigma = WordMorphism(sigma)

src/sage/combinat/matrices/hadamard_matrix.py

@@ -993,12 +993,12 @@ def hadamard_matrix_from_sds(n, existence=False, check=True):
         sage: hadamard_matrix_from_sds(14)
         Traceback (most recent call last):
         ...
-        ValueError: n must be a positive multiple of four.
+        ValueError: n must be a positive multiple of four
     """
     from sage.combinat.designs.difference_family import supplementary_difference_set_hadamard
 
     if n <= 0 or n % 4 != 0:
-        raise ValueError(f'n must be a positive multiple of four.')
+        raise ValueError('n must be a positive multiple of four')
     t = n // 4
 
     if existence:

src/sage/combinat/partition.py

@@ -4201,8 +4201,8 @@ def zero_one_sequence(self):
             sage: all(Partitions().from_zero_one(mu.zero_one_sequence()) == mu for n in range(10) for mu in Partitions(n))
             True
         """
-        tmp = [self[i]-i for i in range(len(self))]
-        return ([Integer(not (i in tmp)) for i in range(-len(self)+1,self.get_part(0)+1)])
+        tmp = [self[i] - i for i in range(len(self))]
+        return [Integer(i not in tmp) for i in range(-len(self) + 1, self.get_part(0) + 1)]
 
     def core(self, length):
         r"""

src/sage/combinat/root_system/root_lattice_realization_algebras.py

@@ -313,14 +313,14 @@ def _test_demazure_operators(self, **options):
                 alphacheck = L.simple_coroots()
                 s = L.simple_reflections()
                 for i in self.cartan_type().index_set():
-                    emalphai = self.monomial(-alpha[i]) # X^{-\alpha_i}
+                    emalphai = self.monomial(-alpha[i])  # X^{-\alpha_i}
                     for weight in L.some_elements():
-                        if not weight.scalar(alphacheck[i]) in ZZ:
+                        if weight.scalar(alphacheck[i]) not in ZZ:
                             # Demazure operators are not defined in this case
                             continue
                         x = self.monomial(weight)
                         result = pi[i](x)
-                        tester.assertEqual(result * (self.one()-emalphai),
+                        tester.assertEqual(result * (self.one() - emalphai),
                                            x - emalphai * x.map_support(s[i]))
             except ImportError:
                 pass

src/sage/combinat/skew_partition.py

@@ -1005,11 +1005,11 @@ def frobenius_rank(self):
             True
         """
         N = len(self[0])
-        mu_betas = [x - j for (j, x) in enumerate(self[1])]
+        mu_betas = [x - j for j, x in enumerate(self[1])]
         mu_betas.extend([- j for j in range(len(self[1]), N)])
         res = 0
         for i, x in enumerate(self[0]):
-            if not x - i in mu_betas:
+            if (x - i) not in mu_betas:
                 res += 1
         return res