[refactor] Use typed NamedTuple for Confidence + PragmaRepresenter (#7718)

The init needs to analyse a string with the old way of doing things,
which is not the best in term of performance. We also have the benefit
of being able to add typing with the new way of doing it.

pylint/interfaces.py

@@ -7,9 +7,8 @@
 from __future__ import annotations
 
 import warnings
-from collections import namedtuple
 from tokenize import TokenInfo
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, NamedTuple
 
 from astroid import nodes
 
@@ -33,7 +32,12 @@ __all__ = (
     "CONFIDENCE_LEVEL_NAMES",
 )
 
-Confidence = namedtuple("Confidence", ["name", "description"])
+
+class Confidence(NamedTuple):
+    name: str
+    description: str
+
+
 # Warning Certainties
 HIGH = Confidence("HIGH", "Warning that is not based on inference result.")
 CONTROL_FLOW = Confidence(

pylint/utils/pragma_parser.py

@@ -5,8 +5,8 @@
 from __future__ import annotations
 
 import re
-from collections import namedtuple
 from collections.abc import Generator
+from typing import NamedTuple
 
 # Allow stopping after the first semicolon/hash encountered,
 # so that an option can be continued with the reasons
@@ -27,7 +27,9 @@ OPTION_RGX = r"""
 OPTION_PO = re.compile(OPTION_RGX, re.VERBOSE)
 
 
-PragmaRepresenter = namedtuple("PragmaRepresenter", "action messages")
+class PragmaRepresenter(NamedTuple):
+    action: str
+    messages: list[str]
 
 
 ATOMIC_KEYWORDS = frozenset(("disable-all", "skip-file"))