🐍 Python Simplified: Understanding Lambda Functions

Lambda functions in Python are concise, anonymous functions defined with the lambda keyword. They are perfect for when you need a quick function without defining a full function using def.

Syntax:

lambda arguments: expression        

Example:

double = lambda x: x * 2 print(double(5)) # Output: 10        

How It Works:

• lambda keyword: Starts the lambda function definition.
• x: Argument (input) to the lambda function.
• : x * 2: Expression that defines what the lambda function does (in this case, multiplies x by 2).

Usage Scenarios:

1. Variable Assignment:

double = lambda x: x * 2        

2. Higher-Order Functions:

numbers = [1, 2, 3, 4, 5]
doubled_numbers = list(map(lambda x: x * 2, numbers))
print(doubled_numbers)  # Output: [2, 4, 6, 8, 10]        

3.Sorting:

students = [
    {'name': 'Alice', 'grade': 90},
    {'name': 'Bob', 'grade': 85},
    {'name': 'Charlie', 'grade': 95}
]

students.sort(key=lambda student: student['grade'], reverse=True)
print(students)
# Output: [{'name': 'Charlie', 'grade': 95}, {'name': 'Alice', 'grade': 90}, {'name': 'Bob', 'grade': 85}]        

Benefits:

• Conciseness: Lambda functions are compact and can be defined in a single line.
• Readability: They make code more readable for simple, one-off operations.
• Functional Programming: Useful in functional-style programming with functions like map, filter, and sorted.

Limitations:

• Single Expression: Lambda functions can only contain one expression, limiting their complexity.
• Use Case: Best suited for quick, simple tasks. For more complex logic or reusable functions, def is preferred.

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Lambda functions are a powerful tool in Python, enabling cleaner and more efficient code for specific use cases