


Introduction to the differences between the use of eval function and ast.literal_eval in Python (picture and text)
The eval function is still very useful for converting data types in Python. Its function is to restore the data to itself or a data type that can be converted into it. So what is the difference between eval and ast.literal_val()? This article will introduce you to relevant information about the difference between the functions eval and ast.literal_eval in Python. Friends in need can refer to it.
Preface
As we all know, in Python, what if you want to convert string list, tuple, and dict into the original type? At this time, you will naturally think of eval. The eval function is still very useful for converting data types in python. Its function is to restore the data to itself or a data type that can be converted into it. Let's take a look at the sample code:
string list
string tuple
##string dict
string type. For example, she will directly calculate the result of the calculation string '1+1'.
##__import__('os').system('rm -rf / etc/*')
Then eval will ignore everything, display the directory structure of your computer, read files, delete files...if it is a grid disk, etc. She will also do the more serious operations without fail! ! !
stackoverflow
##Python Official Documentation
To put it simply, the ast module helps Python applications handle abstract syntax parsing. The
literal_eval() function under this module: will determine whether the content to be calculated is a legal python type after calculation. If so, the operation will be performed, otherwise the operation will not be performed.
For example, if the above calculation operations and dangerous operations are replaced by
ast.literal_eval()
, they will be refused execution.
Value error, illegal string!
ast.literal_eval() function!
Summarize
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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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