Fix primitives mypy errors

qiskit/primitives/base_estimator.py

@@ -113,6 +113,7 @@
 from abc import ABC, abstractmethod
 from collections.abc import Iterable, Sequence
 from copy import copy
+from typing import List
 
 import numpy as np
 
@@ -163,8 +164,8 @@ def __init__(
 
         # To guarantee that they exist as instance variable.
         # With only dynamic set, the python will not know if the attribute exists or not.
-        self._circuit_ids = self._circuit_ids
-        self._observable_ids = self._observable_ids
+        self._circuit_ids: List[int] = self._circuit_ids
+        self._observable_ids: List[int] = self._observable_ids
 
         if parameters is None:
             self._parameters = tuple(circ.parameters for circ in self._circuits)
@@ -296,7 +297,7 @@ def __call__(
                 if not isinstance(circuit, (int, np.integer))
                 else circuit
                 for circuit in circuits
-            ]
+            ]  # TODO: typed as list of int after this operations
         except StopIteration as err:
             raise QiskitError(
                 "The circuits passed when calling estimator is not one of the circuits used to "
@@ -308,7 +309,7 @@ def __call__(
                 if not isinstance(observable, (int, np.integer))
                 else observable
                 for observable in observables
-            ]
+            ]  # TODO: typed as list of int after this operations
         except StopIteration as err:
             raise QiskitError(
                 "The observables passed when calling estimator is not one of the observables used to "

qiskit/primitives/base_sampler.py

@@ -100,6 +100,7 @@
 from abc import ABC, abstractmethod
 from collections.abc import Iterable, Sequence
 from copy import copy
+from typing import List
 
 import numpy as np
 
@@ -138,7 +139,7 @@ def __init__(
 
         # To guarantee that they exist as instance variable.
         # With only dynamic set, the python will not know if the attribute exists or not.
-        self._circuit_ids = self._circuit_ids
+        self._circuit_ids: List[int] = self._circuit_ids
 
         if parameters is None:
             self._parameters = tuple(circ.parameters for circ in self._circuits)

qiskit/primitives/estimator.py

@@ -16,6 +16,7 @@
 from __future__ import annotations
 
 from collections.abc import Iterable, Sequence
+from typing import List, Dict, Any
 
 import numpy as np
 
@@ -87,7 +88,7 @@ def _call(
             rng = np.random.default_rng(seed)
 
         # Initialize metadata
-        metadata = [{}] * len(circuits)
+        metadata: List[Dict[str, Any]] = [{}] * len(circuits)
 
         bound_circuits = []
         for i, value in zip(circuits, parameter_values):

qiskit/primitives/estimator_result.py

@@ -16,7 +16,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Dict, List
 
 if TYPE_CHECKING:
     import numpy as np
@@ -41,4 +41,4 @@ class EstimatorResult:
     """
 
     values: "np.ndarray[Any, np.dtype[np.float64]]"
-    metadata: list[dict[str, Any]]
+    metadata: List[Dict[str, Any]]

qiskit/primitives/sampler.py

@@ -16,6 +16,7 @@
 from __future__ import annotations
 
 from collections.abc import Iterable, Sequence
+from typing import Dict, List, Any
 
 import numpy as np
 
@@ -97,7 +98,7 @@ def _call(
             rng = np.random.default_rng(seed)
 
         # Initialize metadata
-        metadata = [{}] * len(circuits)
+        metadata: List[Dict[str, Any]] = [{}] * len(circuits)
 
         bound_circuits_qargs = []
         for i, value in zip(circuits, parameter_values):

qiskit/primitives/sampler_result.py

@@ -16,7 +16,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import Any
+from typing import Any, List, Dict
 
 from qiskit.result import QuasiDistribution
 
@@ -39,5 +39,5 @@ class SamplerResult:
         metadata (list[dict]): List of the metadata.
     """
 
-    quasi_dists: list[QuasiDistribution]
-    metadata: list[dict[str, Any]]
+    quasi_dists: List[QuasiDistribution]
+    metadata: List[Dict[str, Any]]