How to create higher-order functions in Python?
In Python, a function that takes another function as a parameter or returns a function as output is called a higher-order function. Let's take a look at its features -
This function can be stored in a variable.
This function can be passed as a parameter to another function.
Higher-order functions can be stored in lists, hash tables, etc.
Functions can be returned from functions.
Let’s look at some examples −
Function as Object
The Chinese translation ofExample
is:Example
In this example, these functions are treated as objects. Here, the function demo() is assigned to a variable -
# Creating a function def demo(mystr): return mystr.swapcase() # swapping the case print(demo('Thisisit!')) sample = demo print(sample('Hello'))
Output
tHISISIT! hELLO
Passing functions as parameters
The Chinese translation ofExample
is:Example
Passed as a parameter in this function. demo3() The function calls the demo() and demo2() functions as parameters.
def demo(text): return text.swapcase() def demo2(text): return text.capitalize() def demo3(func): res = func("This is it!") # Function passed as an argument print (res) # Calling demo3(demo) demo3(demo2)
Output
tHIS IS IT! This is it!
Now, let’s discuss decorators. We can use decorators as higher order functions.
Decorators in Python
The Chinese translation ofExample
is:Example
In a decorator, a function is passed as a parameter to another function and then called in the wrapping function. Let’s look at a quick example −
@mydecorator def hello_decorator(): print("This is sample text.")
The above can also be written as -
def demo_decorator(): print("This is sample text.") hello_decorator = mydecorator (demo_decorator)
Decorator example
The Chinese translation ofExample
is:Example
In this example, we will work with decorators as higher-order functions -
def demoFunc(x,y): print("Sum = ",x+y) # outer function def outerFunc(sample): def innerFunc(x,y): # inner function return sample(x,y) return innerFunc # calling demoFunc2 = outerFunc(demoFunc) demoFunc2(10, 20)
Output
Sum = 30The Chinese translation of
Example
is:Example
def demoFunc(x,y): print("Sum = ",x+y) # outer function def outerFunc(sample): def innerFunc(x,y): # inner function return sample(x,y) return innerFunc # calling demoFunc2 = outerFunc(demoFunc) demoFunc2(10, 20)
Output
Sum = 30
Apply syntax decorator
The Chinese translation ofExample
is:Example
The above example can be simplified using a decorator with @symbol. The application of decorators can be simplified by placing the @ symbol before the function we want to decorate -
# outer function def outerFunc(sample): def innerFunc(x,y): # inner function return sample(x,y) return innerFunc @outerFunc def demoFunc(x,y): print("Sum = ",x+y) demoFunc(10,20)
Output
Sum = 30
The above is the detailed content of How to create higher-order functions in Python?. For more information, please follow other related articles on the PHP Chinese website!

There are many methods to connect two lists in Python: 1. Use operators, which are simple but inefficient in large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use the = operator, which is both efficient and readable; 4. Use itertools.chain function, which is memory efficient but requires additional import; 5. Use list parsing, which is elegant but may be too complex. The selection method should be based on the code context and requirements.

There are many ways to merge Python lists: 1. Use operators, which are simple but not memory efficient for large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use itertools.chain, which is suitable for large data sets; 4. Use * operator, merge small to medium-sized lists in one line of code; 5. Use numpy.concatenate, which is suitable for large data sets and scenarios with high performance requirements; 6. Use append method, which is suitable for small lists but is inefficient. When selecting a method, you need to consider the list size and application scenarios.

Compiledlanguagesofferspeedandsecurity,whileinterpretedlanguagesprovideeaseofuseandportability.1)CompiledlanguageslikeC arefasterandsecurebuthavelongerdevelopmentcyclesandplatformdependency.2)InterpretedlanguageslikePythonareeasiertouseandmoreportab

In Python, a for loop is used to traverse iterable objects, and a while loop is used to perform operations repeatedly when the condition is satisfied. 1) For loop example: traverse the list and print the elements. 2) While loop example: guess the number game until you guess it right. Mastering cycle principles and optimization techniques can improve code efficiency and reliability.

To concatenate a list into a string, using the join() method in Python is the best choice. 1) Use the join() method to concatenate the list elements into a string, such as ''.join(my_list). 2) For a list containing numbers, convert map(str, numbers) into a string before concatenating. 3) You can use generator expressions for complex formatting, such as ','.join(f'({fruit})'forfruitinfruits). 4) When processing mixed data types, use map(str, mixed_list) to ensure that all elements can be converted into strings. 5) For large lists, use ''.join(large_li

Pythonusesahybridapproach,combiningcompilationtobytecodeandinterpretation.1)Codeiscompiledtoplatform-independentbytecode.2)BytecodeisinterpretedbythePythonVirtualMachine,enhancingefficiencyandportability.

ThekeydifferencesbetweenPython's"for"and"while"loopsare:1)"For"loopsareidealforiteratingoversequencesorknowniterations,while2)"while"loopsarebetterforcontinuinguntilaconditionismetwithoutpredefinediterations.Un

In Python, you can connect lists and manage duplicate elements through a variety of methods: 1) Use operators or extend() to retain all duplicate elements; 2) Convert to sets and then return to lists to remove all duplicate elements, but the original order will be lost; 3) Use loops or list comprehensions to combine sets to remove duplicate elements and maintain the original order.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

SublimeText3 Mac version
God-level code editing software (SublimeText3)

SublimeText3 English version
Recommended: Win version, supports code prompts!

SublimeText3 Linux new version
SublimeText3 Linux latest version
