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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

Application scenario: Want to iterate a sequence in reverse direction


Solution: Use the built-in reversed() function or implement reversed() on a custom class

Example 1



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)

Example 2



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 +=1

4 .Selective iteration

Application scenario: I want to traverse an iterable object, but I am not interested in some elements at the beginning of it and want to skip


Solution: Use itertools.dropwhile()

Example 1


##

with open(&#39;/etc/passwd&#39;) as f:
  for line in f:
    print(line,end=&#39;&#39;)

Example 2


from itertools import dropwhile
with open(&#39;/etc/passwd&#39;) as f:
  for line in dropwhile(lambda line:line.startwith(&#39;#&#39;),f):
    print(line,end=&#39;&#39;)

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

Detailed explanation of iterator and generator instances in Python

Detailed explanation of iterator and generator instances in Python

Detailed explanation of iterator and generator instances in Python

Detailed explanation of iterator and generator instances in Python##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

Detailed explanation of iterator and generator instances in Python7. 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

Example


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)

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