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Intermediate Python Techniques
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Intermediate Python Techniques

Intermediate Python Techniques

1. Packing and Unpacking
UnpackingPackingPacking and Unpacking UsageChallenge: Dictionary UnpackingChallenge: The Champions League
2. Arguments in Function
Arguments Overview*argsChallenge: Average Mark**kwargsChallenge: kwargs
3. Function as an Argument
High-Order FunctionsLambda FunctionBuilt-in Functions
4. Variable Scope
Global VariableLocal VariableChallenge: Modifying a Global VariableNested FunctionsNonlocal VariableClosuresChallenge: Threshold Checker
5. Decorators
Introduction to DecoratorsSyntaxChallenge: Create Your DecoratorDecorators with ParametersChaining DecoratorsChallenge: Basic Smores RecipePractical Examples of Decorator Usage

bookLambda Function

In Python, lambda functions are anonymous functions defined using the lambda keyword. They are often used for short, single-operation functions without a name, and can be passed as arguments to other functions, just like regular functions.

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              
12345678

            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)
copy
  • apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
  • A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
  • The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Tarefa

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

  1. apply_to_list is our custom function that applies a given function (func) to each element in numbers.
  2. We call apply_to_list twice with different lambda functions.
  3. The first lambda function (lambda x: x + 10) adds 10 to each element.
  4. The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 2
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bookLambda Function

In Python, lambda functions are anonymous functions defined using the lambda keyword. They are often used for short, single-operation functions without a name, and can be passed as arguments to other functions, just like regular functions.

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              
12345678

            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)
copy
  • apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
  • A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
  • The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Tarefa

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

  1. apply_to_list is our custom function that applies a given function (func) to each element in numbers.
  2. We call apply_to_list twice with different lambda functions.
  3. The first lambda function (lambda x: x + 10) adds 10 to each element.
  4. The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 2
toggle bottom row

bookLambda Function

In Python, lambda functions are anonymous functions defined using the lambda keyword. They are often used for short, single-operation functions without a name, and can be passed as arguments to other functions, just like regular functions.

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              
12345678

            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)
copy
  • apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
  • A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
  • The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Tarefa

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

  1. apply_to_list is our custom function that applies a given function (func) to each element in numbers.
  2. We call apply_to_list twice with different lambda functions.
  3. The first lambda function (lambda x: x + 10) adds 10 to each element.
  4. The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

In Python, lambda functions are anonymous functions defined using the lambda keyword. They are often used for short, single-operation functions without a name, and can be passed as arguments to other functions, just like regular functions.

Here's an example demonstrating how to pass a lambda function as an argument to another function:


              
12345678

            
# Define a function that takes a function and a value as arguments
def apply_function(func, value):
    return func(value)

# Call the function with a lambda function as the first argument
result = apply_function(lambda x: x * x, 5)

print(result)
copy
  • apply_function is a function that accepts another function (func) and a value (value), and then applies func to value.
  • A lambda function lambda x: x * x is defined inline and passed as an argument to apply_function. This lambda function squares its input.
  • The apply_function is called with the lambda function and the value 5, resulting in the lambda function squaring 5, which yields 25.

Tarefa

Suppose you have a list of numbers, and you want to apply different operations to the same list, like adding a constant value to each element or multiplying each element by a constant.

  1. apply_to_list is our custom function that applies a given function (func) to each element in numbers.
  2. We call apply_to_list twice with different lambda functions.
  3. The first lambda function (lambda x: x + 10) adds 10 to each element.
  4. The second lambda function (lambda x: x * 2) multiplies each element by 2.

Actually, we are creating our own version of the map function.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 3. Capítulo 2
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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