Python Foundation 13th Day (iterator, generator)

Today's main content:

1. Can iterate objects

2. iterators

3. Generator

1. Can iterate objects

What is an iterative object: An object that contains the __iter__ method internally, which is an iterative object.

View __iter__ Method: Dir (object)

An iterative object follows an iterative protocol.

The iterative objects that have been exposed to are: Str,list,tuple,dict,set,range

Iterator: F1 file handle

How to judge

Law One:

Example: s = ' Laonanhai '

Print (' __iter__ ' in Dir (s))

Law II:

Example: L = [1, 2, 3, 4]
From collections Import Iter

Print (Isinstance (l, iterable))

return Result: # True

2. iterators

What is an iterator

An iterative object can be transformed into an iterator: an object can be iterated. __ITER__ ()---> iterators

Not only contains the __iter__ method, but also contains the __next__ method

Example: L1 = [+ +]

L1_obj = l1.__iter__ ()

Print (' __iter__ ' in Dir (l1_obj)) #True

Print (' __next__ ' in Dir (l1_obj)) #True

To determine the iterator:

Law One:

Print (' __iter__ ' in Dir (l1_obj)) #判断是否是可迭代对象
Print (' __next__ ' in Dir (l1_obj)) #判断是否为迭代器

Law II:
From collections Import Iterator
Print (Isinstance (l1_obj, Iterator))

Benefits of Iterators:

1. Save memory space, only execute the __NEXT__ function, the next step, and load into memory.

2. Meeting Inert machines

3. Can not be repeated value, irreversible.

Example: Simulating a For loop internal mechanism with a while loop

Ideas:

‘‘‘

1. Convert an iterative object into an iterator

2. Internal use of __next__ method, value

3. Using exception handling to deal with the error

‘‘‘

Li = [1,2,3,4,5,6,7]

Li_obj = li.__iter__ ()

While True:

Try

i = li_obj.__next__ ()

Printe (i)

Except Exception:

Break

# Exception means all non-code errors

3. Generator

(1)

What is a generator: The generator is essentially an iterator and is a special iterator. So the iterator has a bit of it.

(2)

How generators are produced:

1. Builder function Constructs

2. Generator derivation constructs

3. Conversion of data types

1. Builder function Constructs

Method:

The function can be transformed into a generator by turning return to yield under the normal function.

Cases:

Def FUNCL ():

Print (666)

Print (555)

Return 777

Print (FUNCL ())

Def FUNCL1 ():

Print (666)

Print (555)

Yield 444

Yleld 777

g = Funcl ()

Print (g)

Conclusion: # <generator object func1 at 0x0000000001197888>

Analytical:

First: As long as there is yield in the function, he is not a function, but a generator.

Second: G is called the generator object

Perform:

Print (g.__next__ ())

Print (g.__next__ ())

Print (g.__next__ ()) #超出yield数量, error

The role of sent

Next, like the Send function, is performed once
Send can assign a value to the previous yield

Cases:

Def generator ():
Print (123)
Content = Yield 1
Print (content)
Print (456)
Yield 2
g = Generator ()
G.__next__ ()
G.send (' Hello ')

Python Foundation 13th Day (iterator, generator)