xxxxxxxxxx
# A generator-function is defined like a normal function,
# but whenever it needs to generate a value,
# it does so with the yield keyword rather than return.
# If the body of a def contains yield,
# the function automatically becomes a generator function.
# Python 3 example
def grepper_gen():
yield "add"
yield "grepper"
yield "answer"
grepper = grepper_gen()
next(grepper)
> add
next(grepper)
> grepper
next(grepper)
> answer
xxxxxxxxxx
def count_to_ten_generator():
for number in range(10):
yield number
my_generator = count_to_ten_generator()
first_number = next(my_generator)
list_or_the_rest = list(my_generator)
xxxxxxxxxx
def my_generator():
for i in range(10):
yield i
for i in my_generator():
print(i)
xxxxxxxxxx
# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
if t:
for x in inorder(t.left):
yield x
yield t.label
for x in inorder(t.right):
yield x
xxxxxxxxxx
# Size of generators is a huge advantage compared to list
import sys
n= 80000
# List
a=[n**2 for n in range(n)]
# Generator
# Be aware of the syntax to create generators, lika a list comprehension but with round brakets
b=(n**2 for n in range(n))
print(f"List: {sys.getsizeof(a)} bits\nGenerator: {sys.getsizeof(b)} bits")
xxxxxxxxxx
def generator_function():
for i in range(10):
yield i
for item in generator_function():
print(item)
# Output: 0
# 1
# 2
# 3
# 4
# 5
# 6
# 7
# 8
# 9
xxxxxxxxxx
def generador():
n = 1
yield n
n += 1
yield n
n += 1
yield n
xxxxxxxxxx
# generator version
def fibon(n):
a = b = 1
for i in range(n):
yield a
a, b = b, a + b