# loguru日志库

## Python - loguru日志库，高效输出控制台日志和日志记录

安装loguru loguru的PyPI地址为：<https://pypi.org/project/loguru/>

GitHub仓库地址为：<https://github.com/Delgan/loguru>

我们可以直接使用pip命令对其进行安装

```bash
pip install loguru 
```

或者下载其源码，使用Python命令进行安装。

loguru简单使用

```bash
from loguru import logger

logger.info("中文loguru")
logger.debug("中文loguru")
logger.error("中文loguru")
logger.warning("中文loguru")
```

运行结果

可以看到其默认的输出格式是包含【时间、级别、模块名、行号以及日志信息】，不需要手动创建 logger ，直接使用即可，另外其输出还是彩色的，看起来会更加友好。

loguru保留日志文件 一般情况，我们都需要将日志输出保存到文件中，loguru直接通过 add() 方法，就可以配置一个日志文件，如下代码所示：

```bash
# coding:utf-8
from loguru import logger

logger.add("interface_log_{time}.log", rotation="500MB", encoding="utf-8", enqueue=True, compression="zip", retention="10 days")
logger.info("中文test")
logger.debug("中文test")
logger.error("中文test")
logger.warning("中文test")
```

然后就去interface\_log\_2020-03-07-15:55.log查看日志

包含知识点

* 第一个参数是保存日志信息的文件路径，像我写的后缀多了个 {time} ，就是获取当前时间节点，这样就会自动创建新的日志；这个time应该是库里自带的变量，如果你想自己定义time也可以的哦，具体可以看看下面封装类的实现形式！
* 当你需要输出中文日志的时候，请加上 encoding="utf-8" ，避免出现乱码
* enqueue=True 代表异步写入，官方的大概意思是：在多进程同时往日志文件写日志的时候使用队列达到异步功效
* rotation 可以理解成日志的创建时机，可以有多种写法
* rotation="500 MB" ：当日志文件达到500MB时就会重新生成一个文件
* rotation="12:00" ：每天12点就会创建新的文件、
* rotation="1 week" ：每隔一周创建一个log
* retention 配置日志的最长保留时间，官方例子： "1 week, 3 days"、"2 months"
* compression 配置文件的压缩格式，可以配置常见的格式 zip、tar、gz、tar.gz 等

loguru字符串输出 最重要的！loguru还提供了字符串格式化输出日志的功能，如下面代码

```bash
logger.info('If you are using Python {}, prefer {feature} of course!', 3.6, feature='f-strings')
n1 = "cool"
n2 = [1, 2, 3]
logger.info(f'If you are using Python {n1}, prefer {n2} of course!')
运行结果
2020-03-07 16:19:25.363 | INFO     | __main__:<module>:43 - If you are using Python 3.6, prefer f-strings of course!
2020-03-07 16:19:25.364 | INFO     | __main__:<module>:46 - If you are using Python cool, prefer [1, 2, 3] of course!
```

可以看到，只要你会Python字符串格式化输出，这个简直信手拈来！

loguru封装类，可以直接拿去用！ 日志输出路径：你的项目路径下的log文件夹下

注意：这个是工具类，需要放在项目路径下的util文件夹之类的，不能直接放项目路径下哈，不然路径会生成错误哦

"""操作日志记录 """

```bash
import time
from loguru import logger
from pathlib import Path

project_path = Path.cwd().parent
log_path = Path(project_path, "log")
t = time.strftime("%Y_%m_%d")


class Loggings:
    __instance = None
    logger.add(f"{log_path}/interface_log_{t}.log", rotation="500MB", encoding="utf-8", enqueue=True,
               retention="10 days")

    def __new__(cls, *args, **kwargs):
        if not cls.__instance:
            cls.__instance = super(Loggings, cls).__new__(cls, *args, **kwargs)

        return cls.__instance

    def info(self, msg):
        return logger.info(msg)

    def debug(self, msg):
        return logger.debug(msg)

    def warning(self, msg):
        return logger.warning(msg)

    def error(self, msg):
        return logger.error(msg)


loggings = Loggings()
if __name__ == '__main__':
    loggings.info("中文test")
    loggings.debug("中文test")
    loggings.warning("中文test")
    loggings.error("中文test")

    logger.info('If you are using Python {}, prefer {feature} of course!', 3.6, feature='f-strings')
    n1 = "cool"
    n2 = [1, 2, 3]
    logger.info(f'If you are using Python {n1}, prefer {n2} of course!')
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://close.gitbook.io/yun-wei-bi-ji/python/python-xiao-ji-qiao/loguru-ri-zhi-ku.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.