104 lines
2.9 KiB
Python
104 lines
2.9 KiB
Python
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# map的使用方法
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"""
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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
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基本语法：
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map(function, iterable, ...)
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function: 要执行的函数（可以是普通函数、匿名函数lambda、内置函数）
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iterable: 一个或多个可迭代对象（列表、元组、字符串、集合等）
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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
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"""
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# 示例
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# 批量转化
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nums1 = ['11', '14', '13', '22']
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result1 = map(int, nums1)
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print(list(result1))
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# 批量计算
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nums2 = [2, 3, 4, 5, 6]
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result2 = map(lambda x: x ** 2, nums2)
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print(list(result2))
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# 多个可迭代对象
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lst1 = [1, 2, 3]
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lst2 = [10, 20, 30]
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result3 = map(lambda x, y: x + y, lst1, lst2)
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print(list(result3))
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# 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
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lst3 = [1, 2, 3]
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lst4 = [10, 20, 30, 40, 50]
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result4 = map(lambda x, y: x + y, lst3, lst4)
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print(list(result4))
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# cmp_to_key的使用方法
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"""
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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。
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基本语法：
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from functools import cmp_to_key
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def compare(a, b):
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# 返回规则
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# -1: a排在b前面
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# 1: a排在b后面
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# 0: a和b位置不变
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if 条件1:
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return -1
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elif 条件2:
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return 1
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else:
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return 0
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sorted_result = sorted(iterable, key=cmp_to_key(compare))
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"""
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# 示例1
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# 对数字列表按绝对值从大到小排序
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from functools import cmp_to_key
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def compare(a, b):
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abs_a = abs(a)
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abs_b = abs(b)
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if abs_a > abs_b:
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return -1 # a的绝对值大，a排前面
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elif abs_a < abs_b:
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return 1 # a的绝对值小，a排后面
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else:
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return 0 # 绝对值相等，位置不变
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nums = [3, -5, 1, -2, 4]
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sorted_nums = sorted(nums, key=cmp_to_key(compare))
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print(sorted_nums)
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# 示例2
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# 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
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students = [
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{"name": "张三", "score": 90, "age": 18},
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{"name": "李四", "score": 85, "age": 19},
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{"name": "王五", "score": 90, "age": 17},
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{"name": "赵六", "score": 88, "age": 20}
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]
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from functools import cmp_to_key
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def cmp(a, b):
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# 先比较分数，降序
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if a["score"] > b["score"]:
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return -1
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elif a["score"] < b["score"]:
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return 1
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else:
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# 分数相同，在比较年龄，升序
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if a["age"] < b["age"]:
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return -1
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elif a["age"] > b["age"]:
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return 1
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else:
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return 0
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sorted_students = sorted(students, key=cmp_to_key(cmp))
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print(sorted_students)
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