


For Python, learning regular rules requires learning how to use the module re. This article will demonstrate some advanced techniques that everyone should master.
Compile regularObject
re.compileFunctionAccording to a patternStringAnd can The selected flag parameter generates a regular expression object. This object has a series of methods for regular expression matching and replacement. There are slight differences in usage. For example, to match a string, you can use the following method:
If you use compile, it will become:
Why do you need to use it like this? In fact, it is to improve the speed of regular expression matching and reuse regular expression objects. Let’s compare the efficiency of the two methods:
You can see that the second method is much faster. In actual work, you will find that the more you use compiled regular expression objects, the better the effect will be.
Group(group)
You may have seen the usage of grouping matching content:
By adding parentheses to the object to be matched, the matching result can be accurately matched. We can also perform nested grouping:
Grouping can meet the needs, but sometimes the readability is poor, then the grouping can be named:
Now the readability is very high.
String matching
Students who have learned sed may have seen the following replacement usage:
This \1 represents the result of the previous regular match. The above sed is to add square brackets to the matched results.
There is also such usage in the re module:
It is also possible to use named grouping:
Look around
re module also supports nearby matching, just look at the example:
When using regular matching function
Most of what we have seen before is matching an expression, but sometimes the requirements are much more complex, especially when replacing.
For example, chat records can be obtained through Slack's API, such as the following sentence:
Among them and are two real users, but Encapsulated by Slack, you need to obtain this correspondence through other interfaces.
The result is similar to this:
After parsing the correspondence, I also hope that the angle brackets are also removed. The result after replacement is "@xiaoming, @laolin Well, it is indeed like this"
How to use regular expressions to achieve this?
So pattern can of course also be a function
The above is the detailed content of Detailed explanation of advanced usage of Python regular expressions. For more information, please follow other related articles on the PHP Chinese website!

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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