What are the log processing and debugging techniques in Python?

What are the log processing and debugging techniques in Python?

Introduction:
In the development and debugging process, the running status of the code, error and exception tracking, and performance evaluation are all crucial. In Python, log processing and debugging skills can help us better understand the execution of the code, locate and fix bugs, and optimize the performance of the program. This article will introduce commonly used log processing libraries and debugging techniques in Python, and provide specific code examples.

1. Log processing skills

1. Use the standard library module logging
   Python’s standard library provides a logging module, which can help developers record logs generated during the running of the program. information. By using different log levels (such as debug, info, warning, error, critical), you can flexibly control the detailed level of log output. The following is a simple example:

import logging

logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

def divide(x, y):
    try:
        result = x / y
        logger.debug("Result of division: %s", result)
        return result
    except ZeroDivisionError:
        logger.error("Cannot divide by zero!")
        return None

divide(10, 2)

In this example, use the basicConfig method to configure the log output level to DEBUG and the output format. Use the getLogger method to create a Logger object named __name__. Debug information is output by calling the debug method of the Logger object, and error information is output by calling the error method.

2. Use third-party library module loguru
   loguru is a powerful and concise log library that provides similar functions to the logging module, but is more convenient and easier to use. It supports a variety of log formats and can output logs to consoles, files, remote servers, etc. according to different needs. The following is a specific example:

from loguru import logger

logger.add("debug.log", level="DEBUG", format="{time} - {level} - {message}")

def divide(x, y):
    try:
        result = x / y
        logger.debug("Result of division: {}", result)
        return result
    except ZeroDivisionError:
        logger.error("Cannot divide by zero!")
        return None

divide(10, 2)

In this example, the logger.add method is used to output the log to a file named debug.log, the level is DEBUG, and the output format is defined . Use logger.debug to output debugging information and logger.error to output error information.

2. Debugging skills

1. Use print statements for simple debugging
   Inserting print statements into the code is one of the simplest and most direct ways to debug. By outputting the values ​​of key variables, it can help developers understand the running process of the code. Here is a simple example:

def divide(x, y):
    print("x =", x)
    print("y =", y)
    try:
        result = x / y
        print("Result of division:", result)
        return result
    except ZeroDivisionError:
        print("Cannot divide by zero!")
        return None

divide(10, 2)

In this example, the values ​​of the variables x and y, as well as the result of the division operation, are output by inserting a print statement.

2. Use the breakpoint debugging tool pdb
   pdb is a debugging tool built into the Python standard library, which can be used for interactive debugging. Developers can insert breakpoints in their code and then run the program into debug mode. In debug mode, you can execute code line by line and view the values ​​of variables. Here is a simple example:

import pdb

def divide(x, y):
    pdb.set_trace()
    try:
        result = x / y
        print("Result of division:", result)
        return result
    except ZeroDivisionError:
        print("Cannot divide by zero!")
        return None

divide(10, 0)

In this example, a breakpoint is inserted in the code by calling the pdb.set_trace method. When running the program, you will enter the pdb debugging mode, and you can debug the code by entering commands (such as n, s, p, etc.).

Conclusion:
The above introduces common log processing and debugging techniques in Python, including using the logging module and loguru library for log processing, and using print statements and pdb tools for debugging. These techniques can help developers better understand the execution of code, quickly locate and fix bugs, and optimize program performance.

By rationally using these techniques, we can improve development efficiency and code quality, so as to better complete Python development work.

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