How to solve Python's function usage irregularity error?

Python is a simple and easy-to-learn programming language. Users can use functions to reuse code and improve programming efficiency. However, sometimes we see some irregular ways of using functions, which not only makes the code difficult to maintain but also leads to a decrease in software quality. This article will introduce how to solve the non-standard function usage error in Python.

1. Function name naming convention

The function name is the identifier when calling the function. In Python, the naming rules for function names follow the following principles:

1.1 Combine verb and noun. Try to use verbs to describe the behavior of the function instead of nouns.

For example, the function name should be written as "print_data" instead of "data". Such naming can allow programmers to clarify the purpose of the function.

1.2 The name should be concise and clear

Use the shortest possible name, but also let the function name restore its function. For example, the function name "rd2hex" can mean converting a numeric value from decimal to hexadecimal.

1.3 Know the meaning after seeing the name

The function name should reflect the meaning of the function. Try not to use ambiguous names, which can help other programmers better understand the code.

2. Use of function parameters

Function parameters are values ​​or variables passed into the function. When using function parameters in Python, you need to pay attention to the following points:

2.1 The number of function parameters

The function should have a specific task, and the function parameters should be as few as possible. If a function has many parameters, it will become difficult to read. If you must use many parameters, consider splitting it into smaller functions and calling them.

2.2 Default values ​​of parameters

In the function definition, you can set the default values ​​of parameters, so that when calling the function, you can omit these parameters and Python will use the default values. Default parameters can make code more concise and reduce programmer errors.

2.3 Parameter type and verification

The type of function parameters can be restricted, which prevents parameters from being passed in values ​​of the wrong type. For example, what happens if the function expects an integer parameter, but the user passes a string? To prevent this, we can add additional safety features like unpacking and type checking.

3. Function readability

The readability of the code is very critical to the function. We should try to make the code easier to read. Below we have compiled several methods to improve the readability of functions.

3.1 Function documentation

In the function definition, use documentation strings to record the functions, parameters, return values ​​and other information of the function so that other programmers can understand the purpose of the function.

3.2 Variable names

Variable names should reflect the particularity of the variable. For example, it is acceptable to use "i" for subscripts within a function, but variables outside the function should use more descriptive names.

3.3 Function length

The function length should be controlled within a readable range as much as possible. If a function uses a long block of statements, it may be difficult to understand and difficult to read.

3.4 Reduce nesting

Reducing nesting can make the code more readable. Although nested functions and if statements are allowed in Python, we should try to avoid excessive nesting, otherwise it will reduce the readability and maintainability of the code.

Conclusion

Functions are an essential part of writing high-quality Python code. When writing a function, you need to consider the naming convention of the function name, type checking of parameters, number of parameters, and documentation strings. If you pay attention to these issues, you can write functions more efficiently and improve the quality of your program.

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