Generator yield in python

Generator yield: Using the yield statement
allows the function to generate a result sequence instead of just a value

def  countdow(n):  
     print("Start!");  
     while n>0:  
          yield n;  
          n -= 1;  
c = countdow(5);  
print(c.__next__())   
print(c.__next__())

Output result:

Start!
5
4

__next__() method Make the generator function run until the next yield statement. At this time, the __next__() method passes the return value to yield and the function temporarily suspends execution
The function continues to execute when __next__() is called again. This process continues until generation until the generator function returns to the end
Usually the __next__() method is not called manually
Instead, a loop is used

for i in  countdow(5):  
 print(i);

Output results:

5
4
3
2
1

The generator is based on processing A powerful way to write programs with pipes, streams or data flows;
Such as:

def tail(f):    
 for line in f:    
  if not line : #如果 非真 则暂时休眠并且再次尝试  
   time.sleep(0.1);  
   continue;  
  yield line; # 将获取到的文件中的值 生成一个序列的值  
filecount = tail(open('E:/work.txt'));  
  
#grep方法 用于在上面方法生成器中查找特定的子字符串    
def grep(lines,searchtext):  
 for line in lines:  
  if searchtext in line :  
   yield  line;  
lines  = grep(filecount,'tom');  #查找带有tom 的子字符串  
for line in lines:   
 print(line);

Output results:
'tom',120,132
Summary:
The role of the generator : When the program runs to yield, the running value
is passed to yield. The program will not output. It can be considered that the program is in a suspended state at this time. When the __next__() method is used, the function continues to execute
until it is encountered again. Go to yield

Advantages: yield does not store a single value, but saves the current program execution status instead of calculating all the elements at once but calculating it once to save memory space

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