A csv.writer with quoting=csv.QUOTE_NONNUMERIC does not quote boolean values, which makes a csv.reader with the same quoting behaviour fail on that value:

-------- csv.py ----------

import csv
import io


f = io.StringIO()

writer = csv.writer(f, quoting=csv.QUOTE_NONNUMERIC)
writer.writerow(['asdf', 1, True])

f.seek(0)
reader = csv.reader(f, quoting=csv.QUOTE_NONNUMERIC)
for row in reader:
    print(row)

----------------------

$ python3 csvbug.py 
Traceback (most recent call last):
  File "csvbug.py", line 12, in <module>
    for row in reader:
ValueError: could not convert string to float: 'True'

----------------------

I'd consider this inconsistency a bug, but in any case something that needs documenting.

boolean is not quoted since in Python it's a subclass of int so True and False are numeric. This is also the case with numeric objects defining __int__ or __float__ but doesn't get a corresponding string representation.

Since QUOTE_NONNUMERIC will converts data to float when reading, I think we may force the converting even when writing so the inconsistency would disappear. Or document this limitation.

This issue is not easy, it needs a thoughtful design before starting coding. I agree with Xiang's analysis and proposed solutions. But if just convert numbers to float we can get an overflow for large integers or lost precision in case of Decimal. The consumer of the CSV file may be not Python and it may support larger precision than Python float.

And it is not clear what would be better solution for enums. Should they be serialized by name or by value?

I would like to solve this issue. 
Is there any other way than casting specifically for the bool object?
(e.g For general ways?)

Oh, I read the Serhiy Storchaka 's comment just right now.