Iterator and generator 181030

I. List Production

[ i*2 for i in range(10) ]

Ii. Generator)

The difference between a generator and a list is that the generator data is generated during the call and cannot be sliced like a list.

• Data is generated only when called.
• Only record the current location

• Only one"Next"Method

  1. Generator 1

>>> (  i*2 for i in range(10)  )>>> for i in b:...     print(i)

2. Next method of Generator

>>> c = (  i*2 for i in range(10)  )>>> c.__next__()0>>> c.__next__()2>>> c.__next__()4

3. Fibonacci Series

# Author:Li Dongfeidef fib(max):    n, a, b = 0, 0, 1    while n < max:        print(b)        a, b = b, a + b        n = n + 1    return "done"fib(100)

4. Change Fibonacci to a generator.

# Author:Li Dongfeidef fib(max):    n, a, b = 0, 0, 1    while n < max:        yield b        a, b = b, a + b        n = n + 1    return "done"f = fib(100)print(f.__next__())print(f.__next__())print(f.__next__())print(f.__next__())print(f.__next__())

5. Capture exceptions

# Author:Li Dongfeidef fib(max):    n, a, b = 0, 0, 1    while n < max:        yield b        a, b = b, a + b        n = n + 1    return "done"f = fib(10)while True:    try:        x = next(f)        print('f:', x)    except StopIteration as e:        print('Generator return value:', e.value)        break

6. Generator parallelism (producer consumer model)

# Author: Li dongfeiimport timedef consumer (name): # Consumer While true: baozi = yield print ("steamed stuffed bun [% s], it was eaten by [% s! "% (Baozi, name) def producer (name): # producer c = Consumer (name) C. _ next _ () For I in range (10): time. sleep (1) print ("made 1 steamed stuffed bun! ") C. Send (I) # Sending I to consumer will be accepted by yield and assigned to baoziproducer (" dongfei ")

Iii. iterator)

• Objects that can directly act on the for loop are collectively referred to as iteration objects: iterable

• The object that can be called by the next () function and continuously return the next value is called the iterator: iterator

  1. determine whether an object can be iterated

>>> from collections import Iterable>>> isinstance([],Iterable)True>>> isinstance((),Iterable)True>>> isinstance('abc',Iterable)True

2. Determine whether it is an iterator object.

>>> from collections import Iterator>>> isinstance(  ( x for x in range(5) ), Iterator  )True

The generator must be an iterator, but not necessarily a generator.

3. Use the ITER () function to convert iterable, such as list, dict, and STR into iterator.

>>> a = [1, 2, 3]>>> b = iter(a)>>> b.__next__()1>>> b.__next__()2>>> b.__next__()3

Iterator and generator 181030