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Detailed explanation of iterator and generator instance methods in Python

Mar 31, 2017 am 09:45 AM

This article mainly introduces the relevant information on detailed examples of iterators and generators in Python. Friends in need can refer to

Python Detailed explanation of iterators and generator examples 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 the iterator

Application scenario: I want to traverse all the elements in an iterableobject, but I don’t want to use a for loop

Solution: Use next()function, and catch the 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
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#test case
items=[1,2,3]
it=iter(items)
next(it)
next(it)
next(it)
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2. Agent iteration

Application scenario: Want to perform an iterative operation directly on a container object containing a list, tuple or other iterable object

Solution: Define an iter() method to perform the iterative operation Proxy to the object inside the container

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)
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#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)
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3. Reverse iteration

Application scenario: Want to iterate a sequence in reverse

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)
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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 <p style="text-align: left;"><strong>4. Selective iteration</strong></p><p style="text-align: left;">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</p><p style="text-align: left;">Solution : Use itertools.dropwhile()</p><p style="text-align: left;">Example 1</p><pre class="brush:php;toolbar:false">with open('/etc/passwd') as f:
  for line in f:
    print(line,end='')
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Example 2

from itertools import dropwhile
with open('/etc/passwd') as f:
  for line in dropwhile(lambda line:line.startwith('#'),f):
    print(line,end='')
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5. Iterate multiple sequences simultaneously

Application scenario: Want to iterate multiple sequences at the same time and take an element from one sequence each time

Solution: Use the zip() function

Detailed explanation of iterator and generator instance methods in Python

Detailed explanation of iterator and generator instance methods in Python

Detailed explanation of iterator and generator instance methods in Python

Detailed explanation of iterator and generator instance methods 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 containers

Solution: Use the itertool.chain() function

Detailed explanation of iterator and generator instance methods in Python

7. Expand nested sequences

Application scenario: Want to expand a multi-level nested sequence into a single-level list

Solution: Use RecursionGenerator containing 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
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#test case
items=[1,2,[3,4,[5,6],7],8]
for x in flatten(items):
  print(x)
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