Python从门到精通(三):高级操作-01-迭代

Python从门到精通(三):高级操作-01-迭代

一、手动创建迭代器

1.1、基础

# 推荐这种写法，而不要用异常来写with open('/etc/passwd') as f: while True: line = next(f, None) if not line: break print(line, end='') num_list = [1, 2, [3, 4, [5, 6], 7], 8]for x in flatten(num_list): print(f'number flatten: {x}')

# 另一种迭代器的写法num_list = [1, 2, 3]items = iter(num_list)for i in range(len(num_list)): print(f'first items next is:{next(items)}')

# 通过stop来停止def manual_iter(): with open('/etc/passwd') as f: try: while True: print(next(f), end='') except StopIteration: passmanual_iter()

"""索引值迭代"""test_list = ['a', 'b', 'c']# 指定索引值从1开始# for idx, str_val in enumerate(test_list, 1):for idx, str_val in enumerate(test_list): print(f'index is: {idx}, str value is: {str_val}')

1.2、实现迭代协议（__iter__方法）

迭代协议要求一个iter()方法返回一个特殊的迭代器对象，这个迭代器对象实现了next()并通过StopIteration异常标识迭代完成。

class Node: def __init__(self, value): self._value = value self._children = [] def __repr__(self): return f'Node({self._value})' def add_child(self, node): self._children.append(node) def __iter__(self): return iter(self._children) def depth_first(self): yield self for c in self: yield from c.depth_first()if __name__ == '__main__': root = Node(0) child_1 = Node(1) child_2 = Node(2) root.add_child(child_1) root.add_child(child_2) child_1.add_child(Node(3)) child_1.add_child(Node(4)) child_2.add_child(Node(5)) for ch in root.depth_first(): print(f'child is: {ch}')

1.3、反向迭代

迭代协议要求一个iter()方法返回一个特殊的迭代器对象，这个迭代器对象实现了next()并通过StopIteration异常标识迭代完成。

1.3.1、确定好大小的集合

#反向迭代只适用于事先确定好大小的集合a = [1, 2, 3, 4]b = list()for x in reversed(a): #这个方法 b.append(x)

1.3.2、不确定好大小的集合

#如果不确定大小，可以放在list中，但比较占空间f = open('/etc/passwd')for line in reversed(list(f)): print(line, end='')#所以需要用自定义方法reversed来优化空间问题class Countdown: def __init__(self, start): self.start = start # Forward iterator def __iter__(self): n = self.start while n > 0: yield n n -= 1 # Reverse iterator def __reversed__(self): n = 1 while n <= self.start: yield n n += 1for rev_val in reversed(Countdown(20)): print(f'reversed order: {rev_val}')for nor_val in Countdown(20): print(f'normal order: {nor_val}')

二、迭代对象的操作

内部含有__iter__方法的对象都是可迭代对象。

num_list = [1, 3, 5, 7, 9]head, *rest = num_list #注意*号的使用，星号表达式永远是列表类型，它表示不确定个数，注意看输出print(f'head is:{head}, rest list is:{rest}') #head is:1, rest list is:[3, 5, 7, 9]

2.1、保留最后N个元素-deque

这个相当于固定大小的管道

from collections import dequedef search(lines, search_val, history=1): """deque当新加入的元素大于固定时，最老的元素会被移除""" previous_lines = deque(maxlen=history) for line in lines: if search_val in line: """yield表达式的用处可以把搜索过程和结果的代码解耦""" yield line, previous_lines previous_lines.append(line)"""这个语法需要注意一下"""if __name__ == '__main__': with open(r'test_file/element.txt') as f: for search_v, prev_lines in search(f, 'python', 2): for pre_line in prev_lines: print(pre_line, end='') print(f'search value is:{search_v}')

2.2、查找最大和最小的N个元素-heapq

import heapqnum_list = [1, 33, 3, 18, 7, -5, 18, 33, 51, -60, 5]print(heapq.nlargest(3, num_list))print(heapq.nsmallest(3, num_list))offer_dict = [ {'company_name': 'IBM', 'stock': 80, 'price': 81.1}, {'company_name': 'AAPL', 'stock': 60, 'price': 113.22}, {'company_name': 'FB', 'stock': 150, 'price': 91.09}, {'company_name': 'HPQ', 'stock': 30, 'price': 79.75}, {'company_name': 'YHOO', 'stock': 50, 'price': 85.35}, {'company_name': 'ACME', 'stock': 100, 'price': 76.65}]cheapest = heapq.nsmallest(3, offer_dict, key=lambda s: s['price'])print(cheapest)

2.3、记录分组-groupby

from operator import itemgetterfrom itertools import groupbydone_record = [ {'done': 'read book', 'date': '07/01/2020'}, {'done': 'work', 'date': '07/04/2020'}, {'done': 'family chat', 'date': '07/02/2020'}, {'done': 'run', 'date': '07/03/2020'}, {'done': 'sport', 'date': '07/02/2020'}, {'done': 'read 20 pages', 'date': '07/02/2020'}, {'done': 'run 5km', 'date': '07/01/2020'}, {'done': 'sport 2 hours', 'date': '07/04/2020'},]# Sort by the desired field firstdone_record.sort(key=itemgetter('date'))# Iterate in groups， groupby扫描整个序列的连续相同的值for date, items in groupby(done_record, key=itemgetter('date')): print(date) for i in items: print(' ', i)"""另一种实现方式，用于分堆后查找"""from collections import defaultdictrecord_by_date = defaultdict(list)for record in done_record: record_by_date[record['date']].append(record)for record in record_by_date['07/01/2020']: print(record)

2.4、排序

sort()和sorted()的区别在于前者会改变原表内容，后面的不会。所以需要有选择的使用

class User(object): def __init__(self, user_id): self.user_id = user_id def __repr__(self): return 'User({})'.format(self.user_id)#自定义排序实现方式1if __name__ == "__main__": users = [User(23), User(3), User(99)] print(users) #[User(23), User(3), User(99)] print(sorted(users, key=lambda u: u.user_id)) #[User(3), User(23), User(99)]#自定义排序实现方式2，推荐 from operator import attrgetter print(sorted(users, key=attrgetter('user_id'))) #[User(3), User(23), User(99)] # by_name = sorted(users, key=attrgetter('last_name', 'first_name')) print(min(users, key=attrgetter('user_id'))) #User(3) print(max(users, key=attrgetter('user_id'))) #User(99)

2.5、命名切片

其实就是把条件定义为一个变量，以便重用

record_str = '......##............20 ....#..1513.5 ........##'#命名切片实现方案NUMBERS = slice(20, 22)PRICE = slice(30, 36)total_cost = int(record_str[NUMBERS]) * float(record_str[PRICE])print(f'total cost is:{total_cost}') #total cost is:30270.0#下面的会原样输出，主要是看下参数的值split_obj = slice(3, 20, 2)print(split_obj.start)print(split_obj.stop)print(split_obj.step)str_obj = 'HelloWorld'split_obj = slice(3, 20, 2)for i in range(*split_obj.indices(len(str_obj))): print(str_obj[i])

版权声明：本文内容由网络用户投稿，版权归原作者所有，本站不拥有其著作权，亦不承担相应法律责任。如果您发现本站中有涉嫌抄袭或描述失实的内容，请联系我们jiasou666@gmail.com 处理，核实后本网站将在24小时内删除侵权内容。