Python builder, List parsing and dictionary parsing

What is a generator

　　Can be understood as data types, the iterator protocol is implemented automatically (other data types need to call their own built-in __iter__ method, so the generator is an iterative object

Generator classification and performance in Python:

1. Generator function: General function definition, return result with yield statement instead of return statement, yield statement returns one result at a time

def Test ():         yield 1        yield 2    # replaces return  position = Test ()print(g)  Print(G.__next__)print(G.__next__)

2. Generator expression: Similar to list pushed to, but generator returns results on demand

　　

# Three -dimensional expression ' Lyg '  'SB'if name = ='lyg'else ' Noob ' Print (RES)

 #   list parsing   Egg_list  = []  for  i in  range (10  '   egg%s  " % i)  print  (egg_list) 
 
 L = [' egg%s '%i for I in Range] 
 # l = [i-I in range ' if i>5] #没有四元 no else 
 print (l) 

# with List resolution L = (' egg%s' for in range)  #  The outside of the generator is expressed in parentheses  instead of the []#  l Generator expression form print(l)print(Next ( L)  #  Next essentially calls __next__print(L.__next__())

Summarize:

1: List-resolved [] replaced by () is the claim that its expression

2: List parsing and builder expressions are all traversal programming, except that generator expressions are more memory-efficient

3:python not only uses the iterator protocol, but makes the for loop more generic. Most built-in functions also use iterator protocols to access objects

 for In range (4))#  instead of  for in range (4)]) 

Generator summary　　

• Syntax is similar to a function
• Status hangs do not wait for the list to be all generated, production one can yield a
• Auto-Return iterator protocol

Yield two features:
　　

• Equivalent to return to do the returned value
• Preserve the running state of a function

Python builder, List parsing and dictionary parsing