In computer science, closure (Closure) is the abbreviation of lexical closure (Lexical Closure), which is a function that references free variables. The referenced free variable will remain with the function even after it has left the environment in which it was created. Therefore, there is another way of saying that a closure is an entity composed of a function and its associated reference environment. Closures can have multiple instances at runtime, and different reference environments and the same function combination can produce different instances.
I prefer the latter, treating closures as a structure for organizing code, for reasons I will explain later.
What is the closure code structure?
In Python, everything is an object, which of course includes functions. Function objects can be assigned to a variable, and the function can be called through this variable; function objects can also be passed as parameters, and can also be used as the return result of a function. Moreover, in Python, functions can be nested.
Python is based on function objects and provides support for the grammatical structure of closures
Let’s look at an example first
def f1(): name1 = 'Alice' name2 = 'Bob' def f2(): print('hello,%s,%s' %(name1,name2)) return f2 if __name__ == '__main__': name1 = 'David' name2 = 'Frank' func = f1() func() print(func.__closure__) print(func.__closure__[0].cell_contents) print(func.__closure__[1].cell_contents)# 输出hello,Alice,Bob (<cell at 0x03A55CF0: str object at 0x03CBEA20>, <cell at 0x03CBEAD0: str object at 0x03CBEAA0>) Alice Bob
Function f2 is defined inside function f1 and is called The variables name1 and name2 defined in f1 are removed.
f1 returns the function object f2, but in fact the returned f2 already includes the variables name1 and name2 in f1. This can be seen from the running results of the code.
In the main program, although name1 and name2 are redefined, the variable value when the function func is executed is still called when it is defined, that is, its reference environment variable, not the variable value when it is used.
To summarize, in Python, a closure is a code block that contains functions and referenced environment variables. I tend to think of closures as a code structure rather than a function, because the first call When it is used, it only wraps the reference environment of the closure and the internal function together, and returns it as a function object, without executing the internal function. When this function object is called, the internal function function will be executed.
The value of the reference environment variable is saved in the closure attribute of the function object. The closure contains a tuple. Each element in this tuple is an object of type cell. We see that the first cell contains Alice, which is the value of the environment variable name1 when we created the closure. This can be seen from the results of the above code.
Now look back and see the encyclopedia’s explanation of closures.
Now, give another example:
# 此例子转自伯乐在线def line_def(a, b): def line(x): return a * x + b return lineif __name__ == '__main__': func = line_def(2, 3) print(func(5))# 输出13
In this example, the function line and the environment variables a, b form a closure. We only need to change the values of a, b to obtain Different straight line functions improve encapsulation, so that we only need to pay attention to the parameters a and b, and do not care about the implementation of the internal straight line.
The biggest feature of closure is that it can bind the variables of the external function to the internal function and return the function after binding the variable (that is, the closure). At this time, even if the environment in which the closure is generated (the external function ) has been released, the closure still exists.
One of the major applications of closures is decorators, but they pass functions. I’ll write this next time.
The above is the detailed content of Detailed introduction to Python closures. For more information, please follow other related articles on the PHP Chinese website!

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.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

WebStorm Mac version
Useful JavaScript development tools

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

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.

Atom editor mac version download
The most popular open source editor