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# map的使用方法
"""
map()函数的核心作用是:将一个函数应用到一个或多个可迭代对象的每个元素上,返回一个迭代器,可理解为批量处理元素的工具
基本语法:
map(function, iterable, ...)
function: 要执行的函数可以是普通函数、匿名函数lambda、内置函数
iterable: 一个或多个可迭代对象(列表、元组、字符串、集合等)
返回值: map对象迭代器需通过list()/tuple()等转为具体序列才能直观查看结果
"""
# 示例
# 批量转化
nums1 = ['11', '14', '13', '22']
result1 = map(int, nums1)
print(list(result1))
# 批量计算
nums2 = [2, 3, 4, 5, 6]
result2 = map(lambda x: x ** 2, nums2)
print(list(result2))
# 多个可迭代对象
lst1 = [1, 2, 3]
lst2 = [10, 20, 30]
result3 = map(lambda x, y: x + y, lst1, lst2)
print(list(result3))
# 可迭代对象不一致时,以最短的可迭代对象为准,超出部分直接忽略
lst3 = [1, 2, 3]
lst4 = [10, 20, 30, 40, 50]
result4 = map(lambda x, y: x + y, lst3, lst4)
print(list(result4))
# cmp_to_key的使用方法
"""
functools.cmp_to_key()是处理自定义排序规则的关键工具核心作用是将传统的比较函数转换为排序所需的key函数让我们能自定义更灵活的排序逻辑。
基本语法:
from functools import cmp_to_key
def compare(a, b):
# 返回规则
# -1: a排在b前面
# 1: a排在b后面
# 0: a和b位置不变
if 条件1:
return -1
elif 条件2:
return 1
else:
return 0
sorted_result = sorted(iterable, key=cmp_to_key(compare))
"""
# 示例1
# 对数字列表按绝对值从大到小排序
from functools import cmp_to_key
def compare(a, b):
abs_a = abs(a)
abs_b = abs(b)
if abs_a > abs_b:
return -1 # a的绝对值大a排前面
elif abs_a < abs_b:
return 1 # a的绝对值小a排后面
else:
return 0 # 绝对值相等,位置不变
nums = [3, -5, 1, -2, 4]
sorted_nums = sorted(nums, key=cmp_to_key(compare))
print(sorted_nums)
# 示例2
# 多条件自定义排序,对学生列表先按分数降序,分数相同再按年龄升序
students = [
{"name": "张三", "score": 90, "age": 18},
{"name": "李四", "score": 85, "age": 19},
{"name": "王五", "score": 90, "age": 17},
{"name": "赵六", "score": 88, "age": 20}
]
from functools import cmp_to_key
def cmp(a, b):
# 先比较分数,降序
if a["score"] > b["score"]:
return -1
elif a["score"] < b["score"]:
return 1
else:
# 分数相同,在比较年龄,升序
if a["age"] < b["age"]:
return -1
elif a["age"] > b["age"]:
return 1
else:
return 0
sorted_students = sorted(students, key=cmp_to_key(cmp))
print(sorted_students)