From 11cba3ddec072373c5953130c4cbfe0eeb7ef21b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fr=C3=A9d=C3=A9ric=20Chapoton?= <chapoton@unistra.fr>
Date: Wed, 5 Feb 2025 10:16:58 +0100
Subject: [PATCH] fixed wrong changes

---
 src/sage/coding/binary_code.pyx             | 15 +++++++--------
 src/sage/rings/finite_rings/integer_mod.pyx |  7 +++----
 2 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/src/sage/coding/binary_code.pyx b/src/sage/coding/binary_code.pyx
index c137cc26932..1b8b1d17ae1 100644
--- a/src/sage/coding/binary_code.pyx
+++ b/src/sage/coding/binary_code.pyx
@@ -3370,8 +3370,8 @@ cdef class BinaryCodeClassifier:
                 # equal to its minimum element
                 v[k] = nu.new_first_smallest_nontrivial(k, W, self.Phi_size * k)
                 if not nu.sat_225(k): hh = k + 1
-                e[k] = 0 # see state 12 and 17
-                state = 2 # continue down the tree
+                e[k] = 0  # see state 12 and 17
+                state = 2  # continue down the tree
 
             elif state == 5:
                 # same as state 3, but in the case where we haven't yet defined zeta
@@ -3381,8 +3381,7 @@ cdef class BinaryCodeClassifier:
                 zb__Lambda_rho[k] = Lambda[k]
                 state = 4
 
-            elif state == 6:
-                # at this stage, there is no reason to continue downward, so backtrack
+            elif state == 6:  # at this stage, there is no reason to continue downward, so backtrack
                 j = k
 
                 # return to the longest ancestor nu[i] of nu that could have a
@@ -3473,7 +3472,7 @@ cdef class BinaryCodeClassifier:
 
                 state = 10
 
-            elif state == 9: # nu is a better guess at the canonical label than rho
+            elif state == 9:  # nu is a better guess at the canonical label than rho
                 rho = PartitionStack(nu)
                 k_rho = k
                 qzb = 0
@@ -3483,7 +3482,7 @@ cdef class BinaryCodeClassifier:
                 zb__Lambda_rho[k+1] = -1
                 state = 6
 
-            elif state == 10: # we have an automorphism to process
+            elif state == 10:  # we have an automorphism to process
                 # increment l
                 if l < self.L-1: l += 1
                 # store information about the automorphism to Omega and Phi
@@ -3504,8 +3503,8 @@ cdef class BinaryCodeClassifier:
                         Omega[ii] ^= (1<<j)  # so cancel
                         j = col_gamma[j]     # cellmates
                     i += 1
-                    while i < ncols and not Omega[ii]&(1<<i): # find minimal element
-                        i += 1                                # of next cell
+                    while i < ncols and not Omega[ii]&(1<<i):  # find minimal element
+                        i += 1                                 # of next cell
                 i = 0
                 jj = self.radix
                 while i < nwords:
diff --git a/src/sage/rings/finite_rings/integer_mod.pyx b/src/sage/rings/finite_rings/integer_mod.pyx
index 67902d41fa4..9a3abc6f963 100644
--- a/src/sage/rings/finite_rings/integer_mod.pyx
+++ b/src/sage/rings/finite_rings/integer_mod.pyx
@@ -1586,15 +1586,14 @@ cdef class IntegerMod_abstract(FiniteRingElement):
                     if all:
                         return [K(s) for s in sign[:2]]
                     return K(sign[0])
-                if all:
-                    modp = [mod(self, 8)]
-                modp = mod(self, 8)
+                modp = [mod(self, 8)] if all else mod(self, 8)
             else:
                 sign = [1]
                 modp = self % p
                 self = self / K(R.teichmuller(modp))
                 modp = modp.nth_root(n, all=all, algorithm=algorithm)
-            # now self is congruent to 1 mod 4 or 1 mod p (for odd p), so the power series for p-adic log converges.
+            # now self is congruent to 1 mod 4 or 1 mod p (for odd p),
+            # so the power series for p-adic log converges.
             # Hensel lifting is probably better, but this is easier at the moment.
             plog = R(self).log()
             nval = n.valuation(p)