ruff updates III

pytket/extensions/cutensornet/backends/cutensornet_backend.py

@@ -313,10 +313,8 @@ def process_circuits(
             raise ValueError(
                 "You must specify n_shots when using CuTensorNetShotsBackend."
             )
-        if type(n_shots) == int:
-            all_shots = [n_shots] * len(circuits)
-        else:
-            all_shots = n_shots  # type: ignore
+
+        all_shots = [n_shots] * len(circuits) if type(n_shots) is int else n_shots
 
         circuit_list = list(circuits)
         if valid_check:
@@ -340,5 +338,5 @@ def _check_all_unitary_or_measurements(circuit: Circuit) -> bool:
             if cmd.op.type != OpType.Measure:
                 cmd.op.get_unitary()
         return True
-    except:
+    except:  # noqa: E722
         return False

pytket/extensions/cutensornet/general_state/tensor_network_convert.py

@@ -159,7 +159,8 @@ def _get_gate_tensors(self, adj: bool = False) -> defaultdict[Any, list[Any]]:
                                 .reshape([2] * (2 * com.op.n_qubits))
                             )
                             self._logger.debug(
-                                f"Adding unitary: \n {permute_rows_cols_in_unitary(com.op.get_unitary(), com_qix_permut).T.conjugate()}"  # type: ignore
+                                f"Adding unitary:\
+\n {permute_rows_cols_in_unitary(com.op.get_unitary(), com_qix_permut).T.conjugate()}"  # type: ignore
                             )
                         else:
                             gate_tensors[i].append(
@@ -168,7 +169,8 @@ def _get_gate_tensors(self, adj: bool = False) -> defaultdict[Any, list[Any]]:
                                 ).reshape([2] * (2 * com.op.n_qubits))
                             )
                             self._logger.debug(  # type: ignore
-                                f"Adding unitary: \n {permute_rows_cols_in_unitary(com.op.get_unitary(),com_qix_permut)}"  # type: ignore
+                                f"Adding unitary:\
+\n {permute_rows_cols_in_unitary(com.op.get_unitary(),com_qix_permut)}"  # type: ignore
                             )
                     break
         self._logger.debug(f"Gate tensors: \n{gate_tensors}\n")
@@ -211,7 +213,8 @@ def _assign_node_tensors(self, adj: bool = False) -> list[Any]:
                     )
                     self._logger.debug(
                         f"criteria: "
-                        f"{(src_ports[0] < src_ports[1]) != (unit_idx[0] < unit_idx[1])}"  # pylint: disable=line-too-long
+                        f"{(src_ports[0] < src_ports[1]) !=
+                            (unit_idx[0] < unit_idx[1])}"  # pylint: disable=line-too-long
                     )
                     if (src_ports[0] < src_ports[1]) != (unit_idx[0] < unit_idx[1]):
                         node_tensors.append(self._gate_tensors[node[1]["desc"]][1])

pytket/extensions/cutensornet/general_state/tensor_network_state.py

@@ -96,7 +96,7 @@ def __init__(
         for com in self._circuit.get_commands():
             try:
                 gate_unitary = com.op.get_unitary()
-            except:
+            except:  # noqa: E722
                 raise ValueError(
                     "All commands in the circuit must be unitary gates. The circuit "
                     f"contains {com}; no unitary matrix could be retrived for it."

pytket/extensions/cutensornet/structured_state/general.py

@@ -229,7 +229,7 @@ def _apply_command(
         elif op.is_gate():  # Either a unitary gate or a not supported "gate"
             try:
                 unitary = op.get_unitary()
-            except:
+            except:  # noqa E722
                 raise ValueError(f"The command {op.type} introduced is not supported.")
 
             # Load the gate's unitary to the GPU memory

pytket/extensions/cutensornet/structured_state/mps_gate.py

@@ -119,10 +119,7 @@ def _apply_2q_unitary(self, unitary: cp.ndarray, q0: Qubit, q1: Qubit) -> MPSxGa
         # S -> shared bond of the gate tensor's SVD
         # a,b,c -> the virtual bonds of the tensors
 
-        if l_pos == positions[0]:
-            gate_bonds = "LRlr"
-        else:  # Implicit swap
-            gate_bonds = "RLrl"
+        gate_bonds = "LRlr" if l_pos == positions[0] else "RLrl"
 
         # Apply SVD on the gate tensor to remove any zero singular values ASAP
         svd_method = tensor.SVDMethod(
@@ -255,10 +252,7 @@ def _apply_2q_unitary_nonadjacent(
         # a,b -> virtual bonds of the MPS
         # m,M -> virtual bonds connected to the "message tensor"
 
-        if l_pos == positions[0]:
-            gate_bonds = "LRlr"
-        else:  # Implicit swap
-            gate_bonds = "RLrl"
+        gate_bonds = "LRlr" if l_pos == positions[0] else "RLrl"
 
         # Apply SVD on the gate tensor to remove any zero singular values ASAP
         svd_method = tensor.SVDMethod(

pytket/extensions/cutensornet/structured_state/mps_mpo.py

@@ -240,10 +240,7 @@ def _apply_2q_unitary(self, unitary: cp.ndarray, q0: Qubit, q1: Qubit) -> MPSxMP
         # s -> virtual bond after QR decomposition
 
         # Assign the bond IDs for the gate
-        if l_pos == positions[0]:
-            gate_bonds = "LRlr"
-        else:  # Implicit swap
-            gate_bonds = "RLrl"
+        gate_bonds = "LRlr" if l_pos == positions[0] else "RLrl"
 
         # Apply SVD on the gate tensor to remove any zero singular values ASAP
         svd_method = tensor.SVDMethod(
@@ -450,11 +447,11 @@ def update_sweep_cache(pos: int, direction: DirMPS) -> None:
                     interleaved_rep.append(r_cached_tensors[-1])
                     r_cached_bonds = self._get_column_bonds(pos + 1, DirMPS.LEFT)
                     interleaved_rep.append(["r", "R"] + r_cached_bonds)
-            elif direction == DirMPS.RIGHT:
-                if pos != 0:  # Otherwise, there is nothing cached yet
-                    interleaved_rep.append(l_cached_tensors[-1])
-                    l_cached_bonds = self._get_column_bonds(pos - 1, DirMPS.RIGHT)
-                    interleaved_rep.append(["l", "L"] + l_cached_bonds)
+            elif direction == DirMPS.RIGHT and pos != 0:
+                # Otherwise, there is nothing cached yet
+                interleaved_rep.append(l_cached_tensors[-1])
+                l_cached_bonds = self._get_column_bonds(pos - 1, DirMPS.RIGHT)
+                interleaved_rep.append(["l", "L"] + l_cached_bonds)
 
             # Figure out the ID of the bonds of the contracted tensor
             if direction == DirMPS.LEFT:

pytket/extensions/cutensornet/structured_state/ttn.py

@@ -161,12 +161,12 @@ def __init__(
 
                 # Calculate the root path of this group
                 path = []
-                for l in reversed(range(n_levels)):
-                    if k < 2**l:
+                for le in reversed(range(n_levels)):
+                    if k < 2**le:
                         path.append(DirTTN.LEFT)
                     else:
                         path.append(DirTTN.RIGHT)
-                        k -= 2**l
+                        k -= 2**le
 
                 # Add each qubit to the qubit_position dictionary
                 for i, q in enumerate(qubits):
@@ -371,7 +371,7 @@ def canonicalise(self, center: RootPath | Qubit, unsafe: bool = False) -> Tensor
         for path in self.nodes:
             # Nodes towards children are closer to the root and coincide in the path
             if len(path) < len(target_path) and all(
-                path[l] == target_path[l] for l in range(len(path))
+                path[le] == target_path[le] for le in range(len(path))
             ):
                 towards_child.append(path)
             # If the center is a physical bond (qubit), its node is skipped

tests/test_utils.py

@@ -40,5 +40,5 @@ def test_device_properties_logger() -> None:
     try:
         with CuTensorNetHandle() as libhandle:
             libhandle.print_device_properties(set_logger("GeneralState", 10))
-    except:
+    except:  # noqa: E722
         pytest.fail("Could not print device properties")