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Detailed explanation of iterator and generator instances in Python
Detailed explanation of iterator and generator instances in Python
This article mainly introduces the relevant information about the detailed explanation of iterator and generator instances in Python. Friends in need can refer to
Detailed explanation of iterator and generator instances in Python
This article summarizes some related knowledge of iterators and generators in Python by focusing on different application scenarios and their solutions, as follows:
1. Manually traverse iterators
Application scenario: Want to traverse all elements in an iterable object, but do not want to use a for loop
Solution: Use the next() function, and Capturing StopIteration exception
def manual_iter():
with open('/etc/passwd') as f:
try:
while True:
line=next(f)
if line is None:
break
print(line,end='')
except StopIteration:
pass#test case items=[1,2,3] it=iter(items) next(it) next(it) next(it)
2. Agent iteration
Application scenario : Want to perform iteration operations directly on a container object containing a list, tuple or other iterable object
Solution: Define an iter() method to proxy the iteration operation to the container inside the container
on the object Example:
##
class Node:
def init(self,value):
self._value=value
self._children=[]
def repr(self):
return 'Node({!r})'.fromat(self._value)
def add_child(self,node):
self._children.append(node)
def iter(self):
#将迭代请求传递给内部的_children属性
return iter(self._children)#test case
if name='main':
root=Node(0)
child1=Node(1)
child2=Nide(2)
root.add_child(child1)
root.add_child(child2)
for ch in root:
print(ch)3. Reverse iteration
a=[1,2,3,4] for x in reversed(a): print(x) #4 3 2 1 f=open('somefile') for line in reversed(list(f)): print(line,end='') #test case for rr in reversed(Countdown(30)): print(rr) for rr in Countdown(30): print(rr)
class Countdown:
def init(self,start):
self.start=start
#常规迭代
def iter(self):
n=self.start
while n > 0:
yield n
n -= 1
#反向迭代
def reversed(self):
n=1
while n <= self.start:
yield n
n +=14 .Selective iteration
##
with open('/etc/passwd') as f:
for line in f:
print(line,end='')Example 2
from itertools import dropwhile
with open('/etc/passwd') as f:
for line in dropwhile(lambda line:line.startwith('#'),f):
print(line,end='')5. Iterate multiple sequences at the same time
Application scenario: Want to iterate multiple sequences at the same time and take an element from one sequence each time
Solution: Use zip() function
##6. Iteration of elements on different collections
Application scenario: Want to perform the same operation on multiple objects, but these objects are in different In the container
Solution: Use itertool.chain() function
7. Expand the nested sequence
Application scenario: Want to expand a multi-level nested sequence into a single-level list
Solution: Use a recursive generator containing a yield from statement
from collections import Iterable
def flatten(items,ignore_types=(str,bytes)):
for x in items:
if isinstance(x,Iterable) and not isinstance(x,ignore_types):
yield from flatten(x)
else:
yield x#test case items=[1,2,[3,4,[5,6],7],8] for x in flatten(items): print(x)
The above is the detailed content of Detailed explanation of iterator and generator instances in Python. For more information, please follow other related articles on the PHP Chinese website!
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