On complex cases, parsing regular expressions takes much, much longer on Python >= 3.7

Example (ipython):

In [1]: import re
In [2]: char_list = ''.join([chr(i) for i in range(0xffff)])
In [3]: long_char_list = char_list * 10
In [4]: pattern = f'[{re.escape(long_char_list)}]'
In [5]: %time compiled = re.compile(pattern)

The test was run on Amazon Linux AMI 2017.03.

On Python 3.6.1, the regexp compiled in 2.6 seconds:
CPU times: user 2.59 s, sys: 30 ms, total: 2.62 s
Wall time: 2.64 s

On Python 3.7.3, the regexp compiled in 15 minutes (~350x increase in this case):
CPU times: user 15min 6s, sys: 240 ms, total: 15min 7s
Wall time: 15min 9s

Doing some profiling with cProfile shows that the issue is caused by sre_parse._uniq function, which does not exist in Python <= 3.6

The complexity of this function is on average O(N^2) but can be easily reduced to O(N).

The issue might not be noticeable with simple regexps, but programs like text tokenizers - which use complex regexps - might really be impacted by this regression.