(EDITED: to add another approach and a more minimal example)

You can use map() with a generator, but it will just try to map generator objects, and it will not try to descend into the generators themselves.

A possible approach is to have a generator do the looping the way you want and have a function operate on the objects.This has the added advantage of separating more neatly the looping from the computation.So, something like this should work:

• Approach #1

# Python 3  (Win10)from concurrent.futures import ThreadPoolExecutorimport osdef read_samples(samples):    for sample in samples:        with open(os.path.join('samples', sample)) as fff:            for _ in range(10):                yield fffdef main():    with ThreadPoolExecutor(10) as exc:        files = os.listdir('samples')        files = list(exc.map(lambda x: str(x.read()), read_samples(files)))        print(str(len(files)), end="\r")if __name__=="__main__":     main()

Another approach is to nest an extra map call to consume the generators:

• Approach #2

# Python 3  (Win10)from concurrent.futures import ThreadPoolExecutorimport osdef read_samples(samples):    for sample in samples:        with open(os.path.join('samples', sample)) as fff:            for _ in range(10):                yield fffdef main():    with ThreadPoolExecutor(10) as exc:        files = os.listdir('samples')        files = exc.map(list, exc.map(lambda x: str(x.read())), read_samples(files))        files = [f for fs in files for f in fs]  # flattening the results        print(str(len(files)), end="\r")if __name__=="__main__":     main()

A more minimal example

Just to get to some more reproducible example, the traits of your code can be written in a more minimal example (that does not rely on files laying around on your system):

from concurrent.futures import ThreadPoolExecutordef foo(n):    for i in range(n):        yield iwith ThreadPoolExecutor(10) as exc:    x = list(exc.map(foo, range(k)))    print(x)# [<generator object foo at 0x7f1a853d4518>, <generator object foo at 0x7f1a852e9990>, <generator object foo at 0x7f1a852e9db0>, <generator object foo at 0x7f1a852e9a40>, <generator object foo at 0x7f1a852e9830>, <generator object foo at 0x7f1a852e98e0>, <generator object foo at 0x7f1a852e9fc0>, <generator object foo at 0x7f1a852e9e60>]

• Approach #1:

from concurrent.futures import ThreadPoolExecutordef foos(ns):    for n in range(ns):        for i in range(n):            yield iwith ThreadPoolExecutor(10) as exc:    k = 8    x = list(exc.map(lambda x: x ** 2, foos(k)))    print(x)# [0, 0, 1, 0, 1, 4, 0, 1, 4, 9, 0, 1, 4, 9, 16, 0, 1, 4, 9, 16, 25, 0, 1, 4, 9, 16, 25, 36]

• Approach #2

from concurrent.futures import ThreadPoolExecutordef foo(n):    for i in range(n):        yield i ** 2with ThreadPoolExecutor(10) as exc:    k = 8    x = exc.map(list, exc.map(foo, range(k)))    print([z for y in x for z in y])# [0, 0, 1, 0, 1, 4, 0, 1, 4, 9, 0, 1, 4, 9, 16, 0, 1, 4, 9, 16, 25, 0, 1, 4, 9, 16, 25, 36]