Detailed explanation of parameters in python functions
When I was reading "Python Core Programming" yesterday, I happened to see the function part, so I will summarize all the centralized parameter types that I have come into contact with so far^^
(1) Positional parameters, when calling the function, pass in the parameters by position
(2) Default parameters , that is, the value of the parameter is given when the function is defined. There are two points to pay attention to when setting the default parameters. First, the required parameters come first and the default parameters come last. The second is to put the parameters with small changes at the end and use them as default parameters. When a function with default parameters is called, the default parameters do not need to be passed in. If the value of the default parameter needs to be changed, the function can be called in the form of assignment. If default parameters are provided out of order, the parameter names need to be written (that is, in the form of assignment). The default parameters must point to unchanged parameters (i.e. unchangedobject, the data inside the object cannot be changed once created, and no locking is required to read the object simultaneously in a multi-tasking environment)
(3) Variable parameters, that is, the number of parameters passed in is variable. Since the number of parameters is uncertain, we can pass the parameters in as a list or tuple, and use for loop to access. If you use variable parameters directly, defining variable parameters only requires adding an * sign in front of the parameters compared to defining list or tuple parameters. The internal parameter of the function receives a tuple, so the function code remains completely unchanged. However, any number of parameters, including 0 parameters, can be passed in when calling the function. If there is already a list or tuple and you want to call a variable parameter, there are two methods. One is to take out each parameter separately and pass it in. The second is to add a * sign in front of it to turn the elements of the list or tuple into variable parameters and pass them in.
(4) Keyword parameters, variable parameters allow you to pass in 0 or any number of parameters, and these parameters are automatically assembled into a tuple when the function is called. Keyword parameters allow you to pass in 0 or any number of parameters with parameter names. These keyword parameters are automatically assembled into a dict inside the function. If the keyword parameter passed in is dict, you can add two ** signs in front of the parameter in the function.
(5) Named keyword parameters are used to limit the names of keywords. Unlike keyword parameters **kw, named keyword parameters require a special separator *, and the parameters following * are regarded as named keyword parameters. If there is already a variable parameter in the function definition, the named parameter that follows does not need a special separator *. Named keyword parameters must be passed in the parameter name, which is different from positional parameters. If no parameter name is passed in, the call will report an error.
Note: The order of definition of parameters is: required parameters, default parameters (immutable objects must be used), variable parameters, named keyword parameters, keyword parameters def f(a,b,c= 0,*,d,**kw), any function can be called in the form similar to fun(*arg,**kw), regardless of how its parameters are defined.
*arg is a variable parameter, arg receives a tuple
**kw is a keyword parameter, kw receives a dict
Variable parameters can be passed directly Input: fun(1,2,3),
You can assemble the list or tuple first, and then pass in *arg: func(*(1,2,3));
Keyword parameters can be passed in directly: fun (a=1, b=2),
You can also assemble the dict first, and then pass it in through **kw: function (**{'a':1,'b':2})
【Related recommendations】
1. <a href="http://www.php.cn/course/list/30.html" target="_self"> Python free video tutorial</a>
2.<a href="http://www.php.cn/course/306.html" target="_self">Marco Education python basic grammar full explanation video</a>
##3. Python basic introductory tutorial<a href="http://www.php.cn/course/32.html" target="_self"></a>
The above is the detailed content of Detailed explanation of parameters in python functions. For more information, please follow other related articles on the PHP Chinese website!

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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


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

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Dreamweaver Mac version
Visual web development tools

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

SublimeText3 Chinese version
Chinese version, very easy to use

WebStorm Mac version
Useful JavaScript development tools

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.