生成器表达式就像一个列表推导，但是它没有找到你感兴趣的所有项目并将它们打包到列表中，而是等待，并逐个生成表达式中的每个项目。
>>> my_list = [1, 3, 5, 9, 2, 6]>>> filtered_list = [item for item in my_list if item > 3]>>> print(filtered_list)[5, 9, 6]>>> len(filtered_list)3>>> # compare to generator expression... >>> filtered_gen = (item for item in my_list if item > 3)>>> print(filtered_gen) # notice it's a generator object<generator object <genexpr> at 0x7f2ad75f89e0>>>> len(filtered_gen) # So technically, it has no lengthTraceback (most recent call last): File "<stdin>", line 1, in <module>TypeError: object of type 'generator' has no len()>>> # We extract each item out individually. We'll do it manually first.... >>> next(filtered_gen)5>>> next(filtered_gen)9>>> next(filtered_gen)6>>> next(filtered_gen) # Should be all out of items and give an errorTraceback (most recent call last): File "<stdin>", line 1, in <module>StopIteration>>> # Yup, the generator is spent. No values for you!... >>> # Let's prove it gives the same results as our list comprehension... >>> filtered_gen = (item for item in my_list if item > 3)>>> gen_to_list = list(filtered_gen)>>> print(gen_to_list)[5, 9, 6]>>> filtered_list == gen_to_listTrue>>>
由于生成器表达式一次只需要产生一项，因此可以节省大量内存。在需要一次获取一项，根据该项进行大量计算然后移至下一项的情况下，生成器表达式最有意义。如果需要多个值，则还可以使用生成器表达式，一次获取几个。如果在程序继续执行之前需要所有值，请改用列表推导。
