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lambda表达式

约 1420 字大约 5 分钟

2026-08-14

Lambda表达式用于创建匿名函数——即没有名称的临时函数。当你需要一个简单函数且只用一次时，lambda能让代码更简洁。

基本语法

lambda 参数1, 参数2, ... : 表达式
# 普通函数
def add(x, y):
    return x + y

# 等价的lambda
add_lambda = lambda x, y: x + y

print(add(2, 3))         # 5
print(add_lambda(2, 3))  # 5

特点：

  • 只能包含一个表达式，不能写多条语句
  • 表达式的计算结果自动返回
  • 通常不命名，即用即走

Lambda vs 普通函数

特性Lambda普通函数 (def)
名称匿名（通常无名字）有函数名
函数体只能有一个表达式可以有多条语句
返回值自动返回表达式结果需要显式 return
适用场景临时、简单的逻辑复杂、复用的逻辑

原则： 逻辑简单且只用一次 → 用lambda；逻辑复杂或需要复用 → 用def。

应用场景：内置高阶函数

高阶函数是指接收函数作为参数的函数。这是lambda最经典的使用场景。

map() — 映射

对可迭代对象的每个元素执行指定操作，返回结果的迭代器。

numbers = [1, 2, 3, 4, 5]

# 普通写法
def square(x):
    return x ** 2

result = map(square, numbers)
print(list(result))  # [1, 4, 9, 16, 25]

# lambda写法——更简洁
result = map(lambda x: x ** 2, numbers)
print(list(result))  # [1, 4, 9, 16, 25]

map() 相当于： 对列表每个元素做"转换"。

# 将字符串列表转为长度列表
names = ["Alice", "Bob", "Charlie"]
lengths = map(lambda s: len(s), names)
print(list(lengths))  # [5, 3, 7]

# 两个列表对应元素相加
a = [1, 2, 3]
b = [10, 20, 30]
sums = map(lambda x, y: x + y, a, b)
print(list(sums))  # [11, 22, 33]

filter() — 过滤

根据条件筛选可迭代对象中的元素，保留满足条件的。

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# 筛选偶数
evens = filter(lambda x: x % 2 == 0, numbers)
print(list(evens))  # [2, 4, 6, 8, 10]

# 筛选长度大于3的字符串
words = ["cat", "elephant", "dog", "butterfly"]
long_words = filter(lambda s: len(s) > 3, words)
print(list(long_words))  # ['elephant', 'butterfly']

filter() 相当于： 按条件"筛选"列表。

# 筛选正数
nums = [-2, -1, 0, 1, 2]
positives = filter(lambda x: x > 0, nums)
print(list(positives))  # [1, 2]

sorted() — 排序（指定key）

sorted() 和列表的 .sort() 都支持 key 参数，用于指定"按什么排序"。

words = ["banana", "pie", "Washington", "book"]

# 按长度排序
sorted_by_len = sorted(words, key=lambda s: len(s))
print(sorted_by_len)  # ['pie', 'book', 'banana', 'Washington']

# 按最后一个字母排序
sorted_by_last = sorted(words, key=lambda s: s[-1])
print(sorted_by_last)  # ['banana', 'pie', 'book', 'Washington']

# 降序排序
sorted_desc = sorted(words, key=lambda s: len(s), reverse=True)
print(sorted_desc)  # ['Washington', 'banana', 'book', 'pie']
# 按绝对值排序
nums = [-5, 2, -8, 1, -9]
sorted_by_abs = sorted(nums, key=lambda x: abs(x))
print(sorted_by_abs)  # [1, 2, -5, -8, -9]

max() / min() — 极值（指定key）

words = ["apple", "banana", "cherry"]

# 找出最长的单词
longest = max(words, key=lambda s: len(s))
print(longest)  # banana

# 找出最短的单词
shortest = min(words, key=lambda s: len(s))
print(shortest)  # apple
students = [
    {"name": "Alice", "score": 85},
    {"name": "Bob", "score": 92},
    {"name": "Charlie", "score": 78}
]

# 找出分数最高的学生
top_student = max(students, key=lambda s: s["score"])
print(top_student)  # {'name': 'Bob', 'score': 92}

reduce() — 累积计算

reduce() 在 functools 模块中，用于将序列逐个累积计算为一个值。

from functools import reduce

numbers = [1, 2, 3, 4, 5]

# 求和
total = reduce(lambda x, y: x + y, numbers)
print(total)  # 15

# 求积
product = reduce(lambda x, y: x * y, numbers)
print(product)  # 120

# 求最大值
maximum = reduce(lambda x, y: x if x > y else y, numbers)
print(maximum)  # 5

作业

基于下面的产品信息完成练习

products = [
  {"name": "iPhone 15", "inc": "APPLE", "price": 5999, "stock": 3012},
  {"name": "MacBook Pro", "inc": "APPLE", "price": 14999, "stock": 580},
  {"name": "AirPods Pro", "inc": "APPLE", "price": 1899, "stock": 4500},
  {"name": "iPad Air", "inc": "APPLE", "price": 4799, "stock": 1200},
  {"name": "Apple Watch", "inc": "APPLE", "price": 2999, "stock": 2100},
  {"name": "Galaxy S24", "inc": "SAMSUNG", "price": 5499, "stock": 2800},
  {"name": "Galaxy Tab", "inc": "SAMSUNG", "price": 3999, "stock": 950},
  {"name": "Galaxy Buds", "inc": "SAMSUNG", "price": 899, "stock": 3200},
  {"name": "Galaxy Watch", "inc": "SAMSUNG", "price": 2199, "stock": 1500},
  {"name": "Mate 60 Pro", "inc": "HUAWEI", "price": 6999, "stock": 800},
  {"name": "MatePad Pro", "inc": "HUAWEI", "price": 4299, "stock": 1100},
  {"name": "FreeBuds", "inc": "HUAWEI", "price": 999, "stock": 2600},
  {"name": "MateBook", "inc": "HUAWEI", "price": 6999, "stock": 670},
  {"name": "Watch GT", "inc": "HUAWEI", "price": 1488, "stock": 1800},
  {"name": "Xiaomi 14", "inc": "XIAOMI", "price": 3999, "stock": 3500},
  {"name": "Redmi K70", "inc": "XIAOMI", "price": 2499, "stock": 4200},
  {"name": "Mi Pad 6", "inc": "XIAOMI", "price": 1999, "stock": 2000},
  {"name": "Mi Band 8", "inc": "XIAOMI", "price": 239, "stock": 8000},
  {"name": "Xiaomi Buds", "inc": "XIAOMI", "price": 499, "stock": 5000},
  {"name": "Xiaomi Book", "inc": "XIAOMI", "price": 4999, "stock": 890},
  {"name": "Pixel 8", "inc": "GOOGLE", "price": 4999, "stock": 600},
  {"name": "Pixel Buds", "inc": "GOOGLE", "price": 1299, "stock": 1500},
  {"name": "Pixel Watch", "inc": "GOOGLE", "price": 2599, "stock": 900},
  {"name": "Pixel Tablet", "inc": "GOOGLE", "price": 3499, "stock": 400},
  {"name": "ThinkPad X1", "inc": "LENOVO", "price": 9999, "stock": 720},
  {"name": "Legion Y9000", "inc": "LENOVO", "price": 8999, "stock": 1100},
  {"name": "Tab P12", "inc": "LENOVO", "price": 2499, "stock": 1300},
  {"name": "Dell XPS 13", "inc": "DELL", "price": 10999, "stock": 650},
  {"name": "Dell G15", "inc": "DELL", "price": 6999, "stock": 1400},
  {"name": "Surface Pro", "inc": "MICROSOFT", "price": 8999, "stock": 580},
  {"name": "Surface Laptop", "inc": "MICROSOFT", "price": 7999, "stock": 700},
  {"name": "Surface Go", "inc": "MICROSOFT", "price": 3999, "stock": 1200},
  {"name": "OnePlus 12", "inc": "ONEPLUS", "price": 4299, "stock": 1800},
  {"name": "OnePlus Buds", "inc": "ONEPLUS", "price": 599, "stock": 3000},
  {"name": "OnePlus Watch", "inc": "ONEPLUS", "price": 1499, "stock": 1600},
  {"name": "OPPO Find X7", "inc": "OPPO", "price": 3999, "stock": 2200},
  {"name": "OPPO Pad 2", "inc": "OPPO", "price": 2999, "stock": 1000},
  {"name": "OPPO Enco", "inc": "OPPO", "price": 499, "stock": 3500},
  {"name": "Vivo X100", "inc": "VIVO", "price": 3999, "stock": 2500},
  {"name": "Vivo Pad 2", "inc": "VIVO", "price": 2499, "stock": 900},
  {"name": "Vivo TWS", "inc": "VIVO", "price": 399, "stock": 4000},
]

充分利用本节课学习过的Lambda表达式和内置高阶函数，完成下面的练习

  1. 按照价格升序排序

  2. 按照价格降序排序

  3. 按照库存总额升序排序（库存总额 = 价格 × 库存数量）

  4. 找出XIAOMI的所有产品，得到一个字符串列表

  5. 找出价格最高的产品所属的公司列表（字符串列表）

  6. 得到每家公司产品的平均价格 结果示例：

    [
    {"inc": "HUAWEI", "avg_price": 4156.8},
    {"inc": "GOOGLE", "avg_price": 3099.0},
    {"inc": "MICROSOFT", "avg_price": 6999.0},
    {"inc": "ONEPLUS", "avg_price": 2132.3333333333335},
    {"inc": "VIVO", "avg_price": 2299.0},
    {"inc": "XIAOMI", "avg_price": 2372.3333333333335},
    {"inc": "SAMSUNG", "avg_price": 3149.0},
    {"inc": "OPPO", "avg_price": 2499.0},
    {"inc": "DELL", "avg_price": 8999.0},
    {"inc": "APPLE", "avg_price": 6139.0},
    {"inc": "LENOVO", "avg_price": 7165.666666666667},
]