Inspired from some of the answers above that work with base python packages I compared the performance of a few (using Python 3.7.3):
Method 1: ast
import ast
list(map(str.strip, ast.literal_eval(u'[ "A","B","C" , " D"]')))
# ['A', 'B', 'C', 'D']
import timeit
timeit.timeit(stmt="list(map(str.strip, ast.literal_eval(u'[ \"A\",\"B\",\"C\" , \" D\"]')))", setup='import ast', number=100000)
# 1.292875313000195
Method 2: json
import json
list(map(str.strip, json.loads(u'[ "A","B","C" , " D"]')))
# ['A', 'B', 'C', 'D']
import timeit
timeit.timeit(stmt="list(map(str.strip, json.loads(u'[ \"A\",\"B\",\"C\" , \" D\"]')))", setup='import json', number=100000)
# 0.27833264000014424
Method 3: no import
list(map(str.strip, u'[ "A","B","C" , " D"]'.strip('][').replace('"', '').split(',')))
# ['A', 'B', 'C', 'D']
import timeit
timeit.timeit(stmt="list(map(str.strip, u'[ \"A\",\"B\",\"C\" , \" D\"]'.strip('][').replace('\"', '').split(',')))", number=100000)
# 0.12935059100027502
I was disappointed to see what I considered the method with the worst readability was the method with the best performance... there are tradeoffs to consider when going with the most readable option... for the type of workloads I use python for I usually value readability over a slightly more performant option, but as usual it depends.