With the widespread application of the Python programming language, developers often encounter the problem of "hard-coded errors" in the process of writing programs. The so-called "hard coding error" refers to writing specific numerical values, strings and other data directly into the code instead of defining them as constants or variables. This approach has many problems, such as low readability, difficulty in maintaining, modifying and testing, and it also increases the possibility of errors. This article discusses how to solve the problem of hard-coded errors in Python functions.
1. What is a hard coding error?
In a Python program, if we write a specific value, string and other data directly into the code, then when the compiler and interpreter execute this code, they need to directly store the data in the The memory address is read out and then operated or processed. This way of writing is called "hard coding", and the corresponding error is called "hard coding error".
2. Why should hard coding errors be avoided?
If there is too much hard-coded data, the reading difficulty and reading experience of the program will be greatly reduced. Because maintainers have to find and change the necessary values one by one in the code, this greatly increases the difficulty of modifying and debugging the code.
Writing specific values directly in the code will cause a lot of trouble for subsequent modifications and maintenance. When requirements change or this value needs to be modified, developers need to find the corresponding lines of code one by one and modify them. This process is not only time-consuming and labor-intensive, but also prone to other problems.
If we directly hardcode it in the code every time we need to use certain data, then there is no way to reuse the data. And if it is defined as a constant or variable, then these data can be used multiple times in other places in the program, greatly improving the utilization of the program.
If you hard-code data directly in the code, it is easy to write wrong values or strings due to manual errors or other reasons. Case. It is not difficult to directly write correct values or strings, but many times the amount of data we need to write is large, or there are some special requirements, so it is very important to avoid manual errors.
3. How to avoid hard coding errors?
So how should we avoid hardcoding errors in Python functions?
If a piece of data needs to be used multiple times in the program, and the value of the data will not change, then we can define a constant and put this Numeric values are stored in constants, which mitigates the impact of hard-coded errors. In Python, we can define constants using the “const” module.
from const import const MY_CONSTANT = const(42)
In this way, we can use MY_CONSTANT
to represent the value 42
throughout the program, and this value will always remain unchanged during runtime.
If the data changes, use the configuration file. We can write the data we need to use into the configuration file, and then read the data in the program. This can effectively avoid various problems caused by hard-coding data in the program. At the same time, you can also freely set the configuration file when running the program, thereby achieving a more flexible effect.
During the running of the program, we may need to use some dynamic variable data. If hard-coded into the program, it will make the program readable performance and maintainability are reduced. Therefore, we can store this data in variables so that it can be set and modified at any time.
Sometimes, we will use the same data in different functions or methods. At this time, we can pass this data as a parameter of the function. . This approach effectively avoids writing the same lines of code repeatedly in multiple functions.
4. Summary
In Python functions, hard-coded errors are a common problem, but through some simple methods, we can effectively avoid the impact of such errors on the program. Methods such as defining constants, using configuration files, using variables, and using function parameters can effectively avoid hard-coded errors, making the program clearer, easier to understand, more maintainable, and reducing the possibility of errors.
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