Briefly talk about closures in Python
Closures in Python
Someone left a message a few days ago, and it is unclear about the use of one of the closures and re.sub. I searched on Script Home and found that I had never written anything related to closures, so I decided to summarize and improve the content of Python.
1. The concept of closure
First of all, we have to start with the basic concept. What is closure? Let’s take a look at the explanation on Wiki:
....
Two key points are mentioned above: free variables and functions. These two keys will be discussed later. I still have to elaborate on the meaning of "closure". As the text makes clear, it can be understood vividly as a closed package. This package is a function. Of course, there is also the corresponding logic inside the function. What is inside the package is freedom. Variables, free variables can wander around with the package. Of course, there must be a premise that this package is created.
For example:
def func(name):
def inner_func(age):
print 'name:', name, 'age:', age
return inner_func
bb = func('the5fire')
bb(26) # >>> name: the5fire age: 26
When func is called here, a closure - inner_func is generated, and the closure holds the free variable - name, so this also means that when the life cycle of function func ends, the variable name still exists. Because it is referenced by the closure, it will not be recycled.
In addition, closure is not a unique concept in Python. All languages that treat functions as first-class citizens have the concept of closure. However, closures can also be used in languages like Java where classes are first-class citizens, but they must be implemented using classes or interfaces.
For more conceptual things, please refer to the reference link at the end.
2. Why use closures
Based on the above introduction, I wonder if readers feel that this thing is somewhat similar to classes. The similarity is that they both provide data encapsulation. The difference is that the closure itself is a method. Just like classes, we often abstract common things into classes when programming (of course, as well as modeling the real world-business) to reuse common functions. The same is true for closures. When we need function-granular abstraction, closures are a good choice.
At this point, a closure can be understood as a read-only object. You can pass a property to it, but it can only provide you with an execution interface. Therefore, in programs we often need such a function object - closure, to help us complete a common function, such as the decorator which will be mentioned later.
3. Use closures
The first scenario, a very important and common usage scenario in Python is the decorator. Python provides a very friendly "syntax sugar" for the decorator - @, which allows us to use the decorator very conveniently. I won’t elaborate too much on the principle of decoration. In short, if you add @decorator_func to a function func, it is equivalent to decorator_func(func):
def decorator_func(func): def wrapper(*args, **kwargs): return func(*args, **kwargs) return wrapper @decorator_func def func(name): print 'my name is', name # 等价于 decorator_func(func)
In this example of the decorator, the closure (wrapper) holds the external func parameter and can accept external parameters. The accepted parameters are passed to func intact and the execution result is returned.
This is a simple example. If it is slightly more complicated, you can have multiple closures, such as the frequently used LRUCache decorator. The decorator can accept parameters like @lru_cache(expire=500). The implementation is the nesting of two closures:
def lru_cache(expire=5): # 默认5s超时 def func_wrapper(func): def inner(*args, **kwargs): # cache 处理 bala bala bala return func(*args, **kwargs) return inner return func_wrapper @lru_cache(expire=10*60) def get(request, pk) # 省略具体代码 return response()
Students who don’t know much about closures must be able to understand the above code. This is an interview question we often asked in previous interviews.
The second scenario is based on a feature of closure-"lazy evaluation". This application is more common when accessing the database, for example:
# 伪代码示意
class QuerySet(object):
def __init__(self, sql):
self.sql = sql
self.db = Mysql.connect().corsor() # 伪代码
def __call__(self):
return db.execute(self.sql)
def query(sql):
return QuerySet(sql)
result = query("select name from user_app")
if time > now:
print result # 这时才执行数据库访问
The above inappropriate example shows the function of lazy evaluation through closure, but the result returned by the above query is not a function, but a class with functional functions. If you are interested, you can take a look at the implementation of Django's queryset. The principle is similar.
The third scenario is the situation where the parameters of a certain function need to be assigned values in advance. Of course, there is already a good solution in Python to access functools.parial, but it can also be achieved using closures.
def partial(**outer_kwargs):
def wrapper(func):
def inner(*args, **kwargs):
for k, v in outer_kwargs.items():
kwargs[k] = v
return func(*args, **kwargs)
return inner
return wrapper
@partial(age=15)
def say(name=None, age=None):
print name, age
say(name="the5fire")
# 当然用functools比这个简单多了
# 只需要： functools.partial(say, age=15)(name='the5fire')
It seems like this is another far-fetched example, but it can be regarded as a practical application of closures.
Finally, to summarize, closures are easy to understand and are widely used in Python. This article is a summary of closures. If you have any questions, please leave a message.
4. References
Wikipedia - Closures
http://stackoverflow.com/questions/4020419/closures-in-python
http://www.shutupandship.com/2012/01/python-closures-explained.html
http://stackoverflow.com/questions/141642/what-limitations-have-closures-in-python-compared-to-language-x-closures
http://mrevelle.blogspot.com/2006/10/closure-on-closures.html
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
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1659
14
1415
52
1309
25
1257
29
1231
24
PHP and Python: Different Paradigms Explained
Apr 18, 2025 am 12:26 AM
PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.
Choosing Between PHP and Python: A Guide
Apr 18, 2025 am 12:24 AM
PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.
PHP and Python: A Deep Dive into Their History
Apr 18, 2025 am 12:25 AM
PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.
Python vs. JavaScript: The Learning Curve and Ease of Use
Apr 16, 2025 am 12:12 AM
Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.
How to run sublime code python
Apr 16, 2025 am 08:48 AM
To run Python code in Sublime Text, you need to install the Python plug-in first, then create a .py file and write the code, and finally press Ctrl B to run the code, and the output will be displayed in the console.
Where to write code in vscode
Apr 15, 2025 pm 09:54 PM
Writing code in Visual Studio Code (VSCode) is simple and easy to use. Just install VSCode, create a project, select a language, create a file, write code, save and run it. The advantages of VSCode include cross-platform, free and open source, powerful features, rich extensions, and lightweight and fast.
Can visual studio code be used in python
Apr 15, 2025 pm 08:18 PM
VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.
How to run python with notepad
Apr 16, 2025 pm 07:33 PM
Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".
