背景#

Lambda匿名函数在Python中经常出现，小巧切灵活，使用起来特别方便，但是小编建议大家少使用，最好多写几行代码，自定义个函数。

既然Python中存在Lambda匿名函数，那么小编本着存在即合理的原则，还是介绍一下，本篇文章翻译自《Lambda Functions in Python》，分享出来供大家参考学习

原文地址：https://www.clcoding.com/2024/03/lambda-functions-in-python.html

案例1：基本语法#

常规函数

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def add(x, y):
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    return x + y

匿名函数

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lambda_add = lambda x, y: x + y

调用2种类型函数

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print(add(3, 5))   #8
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print(lambda_add(3, 5))    #8

案例2：在sorted排序函数中使用匿名函数#

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students = [("Alice", 25), ("Bob", 30), ("Charlie", 22)]
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sorted_students = sorted(students, key=lambda student: student[1])
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print("Sorted Students by Age:", sorted_students)
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#Sorted Students by Age: [('Charlie', 22), ('Alice', 25), ('Bob', 30)]

案例3：在filter过滤函数中使用匿名函数#

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numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9]
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even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
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print("Even Numbers:", even_numbers)
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#Even Numbers: [2, 4, 6, 8]

案例4：在map函数中使用匿名函数#

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numbers = [1, 2, 3, 4, 5]
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squared_numbers = list(map(lambda x: x**2, numbers))
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print("Squared Numbers:", squared_numbers)
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#Squared Numbers: [1, 4, 9, 16, 25]

案例5：在max函数中使用匿名函数#

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numbers = [10, 5, 8, 20, 15]
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max_number = max(numbers, key=lambda x: -x)
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print("Maximum Number:", max_number)
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#Maximum Number: 5

案例6：在sorted排序函数中，多个排序条件#

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people = [{"name": "Charlie", "age": 25},
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          {"name": "Bob", "age": 30},
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          {"name": "Alice", "age": 25}]
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sorted_people = sorted(people,
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                       key=lambda person: (person["age"], person["name"]))
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print("Sorted People:", sorted_people)
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#Sorted People: [{'name': 'Alice', 'age': 25}, {'name': 'Charlie', 'age': 25}, {'name': 'Bob', 'age': 30}]

案例7：在reduce函数中使用匿名函数#

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from functools import reduce
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numbers = [1, 2, 3, 4, 5]
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product = reduce(lambda x, y: x * y, numbers)
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print("Product of Numbers:", product)
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#Product of Numbers: 120

案例8：在条件表达式中使用匿名函数#

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numbers = [10, 5, 8, 20, 15]
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filtered_and_squared = list(map(lambda x: x**2 if x % 2 == 0 else x, numbers))
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print("Filtered and Squared Numbers:", filtered_and_squared)
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#Filtered and Squared Numbers: [100, 5, 64, 400, 15]

历史相关文章#

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