python-iterator, generator and for loop mechanism

One: What is an iterator protocol

1. The iterator protocol means that the object must provide a next method that either returns the next item in the iterator, or causes a Stoplteration exception to terminate the protocol (only backward cannot go forward)

2. An iterative object: An object that implements an iterator protocol (how to: Define an _iter_ () method within an object)

3. The Protocol is a convention that iterates over an object, implements an iterator protocol, and Python's internal tools (such as a For loop, sum,min function, etc.) use an iterator protocol to access an object.

Two: forloop mechanism

The nature of the 1.for loop mechanism: Loop through all objects, all using an iterator protocol.

Three: what is a generator

1. The generator, which can be understood as a data type, automatically implements the iterator protocol (other data types need to call their own built-in _iter_ method), so the generator is an iterative object.

2. Generator classification: There are two representations in Python (Python provides generators in two different ways)

"1" generator function: The general function definition, however, returns the result using the yield statement instead of the return statement, the yield statement returns one result at a time, and in the middle of each result suspends the state of the function so that it can continue execution the next time it leaves.

1 defTest ():2     yield13     yield24     yield35res=Test ()6 Print(RES)7 Print(Res.__next__())8 Print(Res.__next__())9 #Result: <generator Object Test at 0x0000023e254bd8e0>Ten #1 One #2

"2" generator expression: Similar to list derivation, but the generator returns an object that produces results on demand, rather than building a list of results at a time.

1Laomuji= ('Egg%d'%i forIinchRange (10))2 Print(Laomuji)3 Print(Laomuji.__next__())4 Print(Laomuji.__next__())5 Print(Laomuji.__next__())6 Print(Next (Laomuji))7 Print(Next (Laomuji))8 #Result: <generator object <genexpr> at 0x0000015f1262d8e0>9 #Egg 0Ten #Egg 1 One #Egg 2 A #Egg 3 - #Egg 4

3. List Resolution :

1egg_list=[]2  forIinchRange (10):3Egg_list.append ('Egg%d'%i)4 Print(egg_list)5 #results: [' egg 0 ', ' egg 1 ', ' Egg 2 ', ' Egg 3 ', ' Egg 4 ', ' Egg 5 ', ' Egg 6 ', ' Egg 7 ', ' Egg 8 ', ' egg 9 ']6 7 List Resolution:8l=['Egg%d'%i forIinchRange (10)]9 Print(L)Ten #results: [' egg 0 ', ' egg 1 ', ' Egg 2 ', ' Egg 3 ', ' Egg 4 ', ' Egg 5 ', ' Egg 6 ', ' Egg 7 ', ' Egg 8 ', ' egg 9 '] One #list resolution puts the results of the list that will be generated before the for loop is placed behind A  - ternary expression: (three operations, the For loop is preceded by one, for loop is one, if condition this is a) -l1=['Egg%d'%i forIinchRange (10)ifI>5 ] the Print(L1) - #results: [' egg 6 ', ' Egg 7 ', ' Egg 8 ', ' Egg 9 '] - #no four-dollar expression

Summarize:

1. The [] Conversion of the list parsing [] to () is the generator expression

2. List parsing and builder expressions are a convenient way to become, but generator expressions are more memory-saving

3.Python not only uses the iterator protocol to make the For loop more generic. Most built-in functions also use iterator protocols to access objects. For example, the SUM function is a python built-in function that accesses an object using an iterator protocol, and the generator implements an iterator protocol, so we can directly compute a series of worthwhile and:

1  for  in range (4))

Instead of superfluous, construct a list first:

1  for  in range (4)])

python-iterator, generator and for loop mechanism