Detailed explanation of function parameter passing in python
1. Parameter input rules
Variable parameters allow 0 or any number of parameters to be passed in, which will be automatically assembled into a tuple when the function is called;
Keyword parameters allow 0 or any number of parameters to be passed in, which will be automatically assembled into a dict when the function is called;
1. Pass in variable parameters:
def calc(*numbers): sum = 0 for n in numbers: sum = sum + n * n return sum
The functions defined above are used as follows:
Pass in multiple parameters,
calc(1, 2, 3, 4) 30 #函数返回值
Pass in a list,
nums = [1, 2, 3] calc(*nums) # 通过 * 将list中的元素作为可变参数传入函数 14 # 函数返回值
2. Pass in keyword parameters:
>>> def person(name, age, **kw): ... print('name: ', name, 'age: ', age, 'other: ', kw) ... >>> >>> person('luhc', 24, city='Guangzhou') name: luhc age: 24 other: {'city': 'Guangzhou'}
Similarly, a predefined dict can be passed into the above function as a parameter:
>>> info = {'city': 'Guangzhou', 'job': 'engineer'} >>> >>> person('luhc', 24, **info) name: luhc age: 24 other: {'city': 'Guangzhou', 'job': 'engineer'}
Note: The function person obtains a copy of the parameter info. Modification within the function will not affect the value of info
3. In keyword parameters, you can limit the name of keyword parameters:
# 通过 * 分割,以指定关键字参数名 >>> def person(name, age, *, city, job): ... print('name: ', name, 'age: ', age, 'city: ', city, 'job: ', job) ... >>> >>> person('luhc', 24, city='Guangzhou', job='engineer') name: luhc age: 24 city: Guangzhou job: engineer # 如果传入参数中,存在参数名不在定义的范围内,将抛出异常 >>> person('luhc', 24, city='Guangzhou', jobs='engineer') Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: person() got an unexpected keyword argument 'jobs' >>>
In addition, if variable parameters have been specified in the function, * can be omitted, as follows:
# 省略了用 * 作为分割,指定关键字参数名 >>> def person(name, age, *args, city, job): ... print('name: ', name, 'age: ', age, 'args: ', args, 'city: ', city, 'job: ', job) ... >>> >>> person('luhc', 24, 'a', 'b', city='Guangz', job='engineer') name: luhc age: 24 args: ('a', 'b') city: Guangz job: engineer >>> # 同样,如果传入了关键字参数未指定的参数名,则抛出异常 >>> person('luhc', 24, 'a', 'b', city='Guangz', job='engineer', test='a') Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: person() got an unexpected keyword argument 'test' >>>
2. Parameter combination use:
The order of parameter definition must be: required parameters, default parameters, variable parameters, named keyword parameters and keyword parameters
def f1(a, b, c=0, *args, **kw): print('a =', a, 'b =', b, 'c =', c, 'args =', args, 'kw =', kw) def f2(a, b, c=0, *, d, **kw): print('a =', a, 'b =', b, 'c =', c, 'd =', d, 'kw =', kw)
The above is all the content introduced to you in this article. I hope it will be helpful to everyone in understanding the passing of function parameters in Python

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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