This article brings you a brief introduction to closures in Python (with examples). It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you.
1: Introduction
Functional programming is not necessary for programs, but it plays an important role in simplifying programs.
Everything in Python is an object, and functions are also objects
a = 1 a = 'str' a = func
2: Closure
A closure is an entity composed of a function and its related reference environment ( That is: closure = function environment variable)
If in an inner function, a variable in the outer scope (but not in the global scope) is referenced, then the inner function is considered a closure, This is the most straightforward explanation! And the value of this variable will not be modified by the same variable value in the module!
3: The role of closure
Use less global variables. Closure can avoid using global variables
You can call the value inside the function from outside the function:
print(f .__closure__[0].cell_contents)
# Return the value of the environment variable in the closure!
Module operation is not possible!
# ----------------------------------------------# # 闭包 # ----------------------------------------------# # 函数内部定义函数 def curve_pre(): def curve(): print("抛物线") pass return curve # 不能直接调用函数内部的函数 # curve() func = curve_pre() func() def curve_pre1(): a = 25 # 环境变量a的值在curve1外部 def curve1(x): print("抛物线") return a * x ** 2 return curve1 # 返回了的闭包 f = curve_pre1() result = f(2) print(result) # 当在外部定义变量的时候,结果不会改变 a = 10 print(f(2)) print(f.__closure__) # 检测函数是不是闭包 print(f.__closure__[0].cell_contents) # 返回闭包中环境变量的值! # ----------------------------------------------# # 闭包的实例 # ----------------------------------------------# def f1(): m = 10 def f2(): m = 20 # 局部变量 print("1:", m) # m = 20 print("2:", m) # m = 10 f2() print("3:", m) # m = 10,臂包里面的值不会影响闭包外面的值 return f2 f1() f = f1() print(f.__closure__) # 判断是不是闭包 # ----------------------------------------------# # 闭包解决一个问题 # ----------------------------------------------# # 在函数内部修改全局变量的值计算某人的累计步数 # 普通方法实现 sum_step = 0 def calc_foot(step=0): global sum_step sum_step = sum_step + step while True: x_step = input('step_number:') if x_step == ' ': # 输入空格结束输入 print('total step is ', sum_step) break calc_foot(int(x_step)) print(sum_step) # 闭包方式实现----->少使用全局变量,闭包可以避免 def factory(pos): def move(step): nonlocal pos # 修改外部作用域而非全局变量的值 new_pose = pos + step pos = new_pose # 保存修改后的值 return pos return move tourist = factory(0) print(tourist(2)) print(tourist(2)) print(tourist(2))
The above is the detailed content of A brief introduction to closures in Python (with examples). 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