[Python] - Generator

Generator

---

Generator functions allow you to declare a function that behaves like an iterator, it can be used in a for loop.
Generator call like iterator whenever you need

 

1. yield

• if use normal function 'return' get value , but Generator use 'yield'
• yield can be used to control the iteration behaviour of a loop
• instead of building an array containing all the values and returning them all at once, a generator yields the values one at a time

# Genrator
def test_generator() :
    yield 1
    yield 2
    yield 3

test = test_generator()

print(test)
> <generator object test_generator at 0x000002051CA09A80>

print( next(test) )
> 1
print( next(test) )
> 2
print( next(test) )
> 3

2. why use generator?

all the values and returning them all at once, so generator have an advantage.

1. Lazy evaluation(call-by-need)

• evaluation strategy which delays the evaluation of an expression until its value is needed and which also avoids repeated evaluations

 

2. memory efficiency

• Generator use Lazy evaluation, this stargegy Only use memory as needed

3. Difference List comprehension and generator comprehension

if num value bigger and bigger so n = 100 , list comprehension result after 100 time but generator result every second.

import time
def sleep_func(num) :
    print('sleep')
    time.sleep(1)

    return num

# test list_comprehension
list = [sleep_func(i) for i in range(5)]
for i in list:
    print(i)
"""
sleep
sleep
sleep
sleep
sleep
0
1
2
3
4
"""

# test generator_comprehension
gen = (sleep_func(i) for i in range(5))
for i in gen:
    print(i)
"""
sleep
0
sleep
1
sleep
2
sleep
3
sleep
4
"""

 

3. yield from 

• if you want list to generator use 'yield from' command.

def yield_abc():
  for ch in ["A", "B", "C"]:
    yield ch

# right this
def yield_abc():
  yield from ["A", "B", "C"]

4. generator comprehension

• generator comprehesion similar list comprehension. difference is '[]' to '()'.

gen = (ch for ch in "ABC")
> <generator object <genexpr> at 0x0000017E292C82E0>