Introduction
The function is a callable unit containing instructions, aimed at reducing code duplication and organizing complex tasks. There are two types: void functions (no return value) and those that return a value.
This is the basic structure of function in Python.
def function_name(args): function body
This is an example of a void function (no return value) in Python.
# create a function def hello(): print("hello!") # call the function hello()
Output
hello!
Based on the code above, the function called hello() is created. The function is called by specifying the function name followed by parentheses ().
This is an example of fa unction with the return value.
# create a function with return value def add(a,b): return a + b result = add(2,4) print(result)
Output
6
Based on the code above, the function called add() is created to sum two numbers. The return value of the add() function is stored inside the result variable.
When working with the return value function, ensure the returned value is being used.
Arguments and Keyword Arguments
The function in Python can take multiple arguments dynamically. There are two approaches to implementing multiple arguments in a function:
Arguments: the multiple arguments are implemented in a function without specifying the keywords. the arguments can be implemented using *args.
Keyword arguments: the multiple arguments are implemented in a function with the specified keywords. the keyword arguments can be implemented using **kwargs.
Both arguments and keyword arguments must be located in the last position of the argument definition in a function.
This is an example of multiple arguments implementation using the arguments approach to calculate the sum of the numbers dynamically.
def sum(*args): result = 0 for arg in args: result += arg return result print(sum(1,2)) print(sum(1,2,3)) print(sum(1,2,3,4,5,4,3,2))
Output
3 6 24
Based on the code above, the sum() function can be called with a different number of parameters.
This is an example of multiple arguments implementation using the keyword arguments approach.
def display_info(name,**kwargs): print("========") print(f"name: {name}") print("other informations") for k, val in kwargs.items(): print(f"{k}: {val}") print("========") display_info("john",job="programmer",company="acme inc") display_info("doe",job="programmer",company="acme inc",skills="go,java,php")
Output
======== name: john other informations job: programmer company: acme inc ======== ======== name: doe other informations job: programmer company: acme inc skills: go,java,php ========
Based on the code above, the display_info() function can be called with a different number of parameters. By using **kwargs, the parameters can be defined with the keywords.
Both arguments and keyword arguments can be used together. This is an example.
def display(*args,**kwargs): print("===========") print("items") for arg in args: print(arg) print("other information") for k, val in kwargs.items(): print(f"{k}: {val}") print("===========") display("apple","coffee","milk",payment="cash") display("TV","Camera",payment="cash",delivery="express")
Output
=========== items apple coffee milk other information payment: cash =========== =========== items TV Camera other information payment: cash delivery: express ===========
Recursive Function
The recursive function is a function that calls itself when accomplishing its task. The recursive function can solve many problems including factorial numbers, the Fibonacci sequence, and others.
There are two main components in a recursive function:
- Base case: the base case defines when the function is stopped.
- Recurrence relation: the recurrence relation defines the recursive process of the function.
In this example, the factorial calculation is implemented using a recursive function.
def function_name(args): function body
Output
# create a function def hello(): print("hello!") # call the function hello()
Let's take a closer look to the factorial() function. There are two components involved in this function:
base case: the function execution terminates if the value of n equals to 0 or 1.
recurrence relation: the function executes if the value of n greater than 1.
hello!
The factorial() function is illustrated in this picture below.
Lambda
The lambda is an anonymous function. The lambda can contain many arguments just like function in general. The lambda function is suitable for creating a small function that returns the value directly.
This is an example of the sum() function.
# create a function with return value def add(a,b): return a + b result = add(2,4) print(result)
This is the example of a lambda function to sum two numbers. The lambda function is stored inside a variable called sum_func.
6
To use the lambda function, call the function by its variable name.
def sum(*args): result = 0 for arg in args: result += arg return result print(sum(1,2)) print(sum(1,2,3)) print(sum(1,2,3,4,5,4,3,2))
Map and Filter
Map Function
The map() function executes a provided callback function for each item inside a list.
This is the example of the map() function to multiply each number by 3.
3 6 24
Output
def display_info(name,**kwargs): print("========") print(f"name: {name}") print("other informations") for k, val in kwargs.items(): print(f"{k}: {val}") print("========") display_info("john",job="programmer",company="acme inc") display_info("doe",job="programmer",company="acme inc",skills="go,java,php")
Based on the code above, the triple() function acts as a callback for the map() function which means the triple() function is called for each item in the numbers list. Then, the result of the map() function is converted into the list and then stored inside the variable called result.
The example above can be simplified using the lambda function.
======== name: john other informations job: programmer company: acme inc ======== ======== name: doe other informations job: programmer company: acme inc skills: go,java,php ========
Output
def display(*args,**kwargs): print("===========") print("items") for arg in args: print(arg) print("other information") for k, val in kwargs.items(): print(f"{k}: {val}") print("===========") display("apple","coffee","milk",payment="cash") display("TV","Camera",payment="cash",delivery="express")
Filter Function
The filter() function selects the item inside a list based on the given callback function. The filter() function is suitable for filtering the items inside a list by using the provided callback function. The filter() function requires a callback function that returns a boolean value.
This is the example of the filter() function to select only even numbers in a list.
=========== items apple coffee milk other information payment: cash =========== =========== items TV Camera other information payment: cash delivery: express ===========
Output
def factorial(n): if n == 0 or n == 1: return 1 else: return n * factorial(n-1) # call the function result = factorial(5) print(result)
Based on the code above, the filter() function uses is_even() as a callback function to select the even numbers from the list.
This example can be simplified using the lambda function.
120
Output
def function_name(args): function body
Example - Remove Duplicate Codes
The function can be used to remove duplicate codes. For example, there are two functions called register() and login(). Both functions is using the validation process.
# create a function def hello(): print("hello!") # call the function hello()
There is a duplicate code for the validation process. To remove these duplicates, the validation process can be wrapped in a separate function.
hello!
The validate() function can be used inside the register() and login() functions.
# create a function with return value def add(a,b): return a + b result = add(2,4) print(result)
Based on the code above, the code is cleaner and easier to modify because if the additional validation rules are updated, the validation rules can be updated in one place (inside the validate() function).
Tips
These are the key tips when working with a function in Python.
The function must complete a single task. If multiple tasks are required, create a separate function for other tasks.
The maximum number of function arguments is 3. If the arguments seem more than 3, consider using a dedicated data object for the function argument.
The maximum number of function arguments seems debatable.
This is the example of the create_account() function using arguments.
6
The create_account() function can be modified to use data object for cleaner code.
def sum(*args): result = 0 for arg in args: result += arg return result print(sum(1,2)) print(sum(1,2,3)) print(sum(1,2,3,4,5,4,3,2))
- Use documentation to explain the function description. The documentation can be added using """ syntax.
This is an example of using documentation inside a function.
3 6 24
Sources
- Arguments and keyword arguments in function
- Recursive function illustrations
I hope this article helps you learn Python. If you have any feedback, please let me know in the comment section.
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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