Lambda Functions in python

 # Lambda Functions

lambda_function = lambda parameter: expression

Lambda functions, also known as anonymous functions, are small, one-line functions that can have multiple arguments but can only have one expression. They are useful when you need a simple function for a short duration and don't want to define a full-fledged function using the `def` keyword. Lambda functions are typically used in situations where a function is required as an argument to another function, like `map()`, `filter()`, or `sort()`. Let's explore some examples of lambda functions in Python:

Example 1: Creating a basic lambda function to add two numbers:

```python
add = lambda x, y: x + y
result = add(5, 10)
print(result)  # Output: 15
```

Example 2: Using lambda with `map()` to apply a function to each element of a list:

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

# Doubling each element using a lambda function
doubled_numbers = list(map(lambda x: x * 2, numbers))
print(doubled_numbers)  # Output: [2, 4, 6, 8, 10]
```

Example 3: Using lambda with `filter()` to filter elements based on a condition:

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

# Filtering even numbers using a lambda function
even_numbers = list(filter(lambda x: x % 2 == 0, numbers))
print(even_numbers)  # Output: [2, 4, 6, 8, 10]
```

Example 4: Sorting a list of tuples based on a specific element using lambda:

```python
students = [("Alice", 23), ("Bob", 20), ("Charlie", 25)]

# Sorting based on the second element of each tuple (age)
sorted_students = sorted(students, key=lambda x: x[1])
print(sorted_students)  # Output: [('Bob', 20), ('Alice', 23), ('Charlie', 25)]
```

Lambda functions are concise and serve well for simple operations. However, they should be used judiciously, and complex operations are better suited for regular functions defined with `def`. Lambda functions are limited to a single expression and can't contain statements or multiple lines of code.