Implement models for searx/answerers

sort froms

Import List from typing to support Python 3.8

Use SearchQuery model

Remove list for List

use Dict instead of dict

Use RawTextQuery instead of SearchQuery, type a dict, and remove unecessary str() method in webapp

improve docstring, remove test code

Implement a BaseQuery class and use that, improve answerer tests based on updated types

Add back sys

fix new linting issues

add space

Update answerer.py - use dict

use future annotations

use BaseQuery for RawTextQuery

searx/answerers/statistics/answerer.py

@@ -1,49 +1,51 @@
 # SPDX-License-Identifier: AGPL-3.0-or-later
+
+from __future__ import annotations
 from functools import reduce
 from operator import mul
 
 from flask_babel import gettext
+from typing import Callable
+from searx.answerers.models import AnswerDict, AnswerSelfInfoDict
+from searx.search.models import BaseQuery
 
 
 keywords = ('min', 'max', 'avg', 'sum', 'prod')
 
 
+stastistics_map: dict[str, Callable[[list[float]], float]] = {
+    'min': lambda args: min(args),
+    'max': lambda args: max(args),
+    'avg': lambda args: sum(args) / len(args),
+    'sum': lambda args: sum(args),
+    'prod': lambda args: reduce(mul, args, 1),
+}
+
+
 # required answerer function
 # can return a list of results (any result type) for a given query
-def answer(query):
+def answer(query: BaseQuery) -> list[AnswerDict]:
     parts = query.query.split()
 
     if len(parts) < 2:
         return []
 
     try:
-        args = list(map(float, parts[1:]))
-    except:
+        args: list[float] = list(map(float, parts[1:]))
+    except Exception:
         return []
 
     func = parts[0]
-    answer = None
 
-    if func == 'min':
-        answer = min(args)
-    elif func == 'max':
-        answer = max(args)
-    elif func == 'avg':
-        answer = sum(args) / len(args)
-    elif func == 'sum':
-        answer = sum(args)
-    elif func == 'prod':
-        answer = reduce(mul, args, 1)
-
-    if answer is None:
+    if func not in stastistics_map:
         return []
 
-    return [{'answer': str(answer)}]
+    return [{'answer': str(stastistics_map[func](args))}]
 
 
 # required answerer function
 # returns information about the answerer
-def self_info():
+def self_info() -> AnswerSelfInfoDict:
     return {
         'name': gettext('Statistics functions'),
         'description': gettext('Compute {functions} of the arguments').format(functions='/'.join(keywords)),