Logging Errors Like a PRO in Python Made Easy

00:05:20
https://www.youtube.com/watch?v=ulCL6JcCBI4

摘要

TLDRIn this video, learn how to effectively use Python's built-in logging module to streamline the debugging process in your Python applications. The session starts by explaining the basic setup steps: importing the logging module, creating a logger instance using logging.getLogger, and setting up handlers (Console and RotatingFileHandler) to direct where log messages go. Customizing the format of log messages enhances readability and aids in tracking the events accurately. You'll understand the significance of configuring log levels to filter messages, such as setting a console handler to display only warnings and errors, while a rotating file handler logs only errors. This helps manage log files efficiently by preventing them from becoming too large. The video then progresses to showcasing an example using a function that reads a file, demonstrating error handling by logging messages when errors occur, both to the console and to a log file. This approach provides a reliable method to trace problems while maintaining organized logs for future analysis. In summary, Python logging is a powerful tool for any serious Python project.

心得

  • 🔍 Using Python logging can significantly simplify debugging.
  • 🖥️ Handlers determine where logging messages are outputted.
  • ⚖️ Log levels help filter which messages are recorded or displayed.
  • 📜 Formatting logs improves readability and information clarity.
  • 🔄 RotatingFileHandler helps manage log file sizes efficiently.
  • 🔧 BasicConfig can configure logging settings compactly.
  • ⚠️ ConsoleHandler can be set for warnings and errors only.
  • 📝 Errors are written both to console and files using handlers.
  • 📁 Logging is crucial for managing production environment errors.
  • 🛠️ Example code provided showcases handling of file errors.

时间轴

  • 00:00:00 - 00:05:20

    The video introduces Python Logging as a tool to improve debugging by tracking issues, saving error messages, and customizing logs for insights. A logger instance is created using `logging.getLogger`, allowing specific logging for each file. Handlers like Console Handler and Rotating File Handler control where log messages are sent, with limitations on file size to keep logs organized. The importance of logging in Python projects is emphasized, especially for monitoring code execution and troubleshooting.

思维导图

视频问答

  • What is the main benefit of using Python's logging module?

    Python's logging module helps in tracking what happens in a code during runtime, catching potential issues before they lead to bigger problems.

  • What is a handler in Python logging?

    A handler determines where your log messages are sent, like to the console or a file.

  • How can you prevent log files from becoming too large?

    By using the RotatingFileHandler, which creates a new log file once the current file reaches a specified size.

  • What is the purpose of log levels?

    Log levels help determine which messages are sent to which handlers.

  • How can you format log messages?

    You can use the Logging.Formatter class to customize log messages with timestamps, log level, message, etc.

  • Can you configure logging in a more compact way?

    Yes, using the basicConfig function allows you to set the level, format, and handlers more compactly.

查看更多视频摘要

即时访问由人工智能支持的免费 YouTube 视频摘要！
字幕
en
自动滚动:
  • 00:00:00
    Hello, Pythoneer! Want to make your Python apps easier to debug and
  • 00:00:03
    maintain? Then stick around as we walk through Python Logging Explained, a
  • 00:00:08
    quick guide to better debugging. In this video, you'll learn how to keep track of
  • 00:00:13
    issues in your code, save error messages to a file, and even customize logs for
  • 00:00:18
    better insights. What if I told you a few lines of code could make debugging
  • 00:00:22
    10 times easier? By the end of this video, you'll know exactly how to do it.
  • 00:00:27
    Let's start with the basics, and later on we check out a real code example.
  • 00:00:31
    Alright, so first we need to import Python's built-in logging module,
  • 00:00:35
    because we will use this here in this video. Next, we create a logger instance
  • 00:00:39
    by calling logging.getLogger. This gives us a custom logger named after the
  • 00:00:44
    current module, which means we can create specific logging behaviors for
  • 00:00:48
    each file in our project, called name for example. Now, let's add some
  • 00:00:52
    handlers. A handler controls where our log messages go. Here, I'm creating two
  • 00:00:57
    handlers. Console Handler, using the StreamHandler class that sends messages
  • 00:01:02
    to the console, we could use the normal FileHandler class here like shown, but I
  • 00:01:06
    would suggest you to better use the RotatingFileHandler. This needs to be
  • 00:01:10
    imported separately. The RotatingFileHandler, using the
  • 00:01:14
    RotatingFileHandler class, sends the messages to a file named, e.g., app.log.
  • 00:01:20
    It can be limited in file size, e.g. 2000 bytes, meaning it'll create a new
  • 00:01:25
    file once it reaches that size. This way, our logs stay organized, and we
  • 00:01:30
    avoid creating massive log files. Let's take a short break. We didn't talk about
  • 00:01:35
    yet why it's worth adding a logger to your profile. Using a logging module
  • 00:01:40
    like this is crucial for any serious Python project. Logs help you monitor
  • 00:01:45
    what's happening in your code while it's running, and catch problems that may not
  • 00:01:49
    cause immediate errors, but could lead to bigger issues later. For example,
  • 00:01:55
    logging is great for tracking user actions in web apps, recording system
  • 00:01:59
    errors in production environments, or troubleshooting background tasks in data
  • 00:02:04
    processing scripts. With handlers set up, we need to set the log levels. Log
  • 00:02:09
    levels determine which messages are sent to each handler. Here, I'm setting
  • 00:02:14
    Console Handler to Warning, so warning and error messages show up in the
  • 00:02:18
    console. For Rotating File Handler, I'm setting it to Error, meaning only error
  • 00:02:23
    messages will be saved to the log file. Next, we can customize our log messages
  • 00:02:28
    with a formatter. A clear format makes it easy to understand what happened and
  • 00:02:32
    when. You can run the help function on the Logging.Formatter class to see
  • 00:02:37
    available variables you can access. Here, you can also see all you can do on
  • 00:02:41
    the formatting. Check it out. Mine here is the basic example to you. This format
  • 00:02:47
    string here tells Python to include the timestamp, logger name, log level, and
  • 00:02:52
    the actual message. As I finish up the format string, let me know if you're
  • 00:02:57
    enjoying the video. If so, please like, subscribe, and drop any feedback in the
  • 00:03:02
    comments. Next step is to apply this logging format to the two handlers
  • 00:03:06
    console and rotating file using the set formatter function. To complete the
  • 00:03:11
    setup, we attach our handlers to the logger using the add handler function.
  • 00:03:16
    Adding these handlers ensures that the logger knows where to send messages
  • 00:03:20
    based on the levels we configured. Now we're ready to log messages. Here's an
  • 00:03:25
    example. I'll log a warning message and an error message that I use the warning
  • 00:03:30
    and error function to manual rise it. When I run this code, the warning
  • 00:03:35
    appears in the console while the error appears in the console and is
  • 00:03:39
    additionally saved to This approach is great for tracking issues as they happen
  • 00:03:45
    and storing critical errors for later analysis. And that's it for the basics.
  • 00:03:50
    Now it's time to talk about how you could use this embedded in your code
  • 00:03:54
    without creating manual errors, like I did here. Therefore, I prepared some
  • 00:03:59
    code for you. I want to walk you through. In the example, we raise and
  • 00:04:03
    handle errors when we try to open a file that doesn't exist. The first big change
  • 00:04:07
    you can see here is that you can configure the logging away more compact
  • 00:04:12
    using the basic config function. Here we can set the level, the format and the
  • 00:04:17
    handlers to store an error in a file and see it in the console. Then I created a
  • 00:04:21
    function called read file, which takes a file as input. Inside here, I use the
  • 00:04:26
    try accept syntax to catch and handle errors, try to open the file, read it
  • 00:04:31
    and return data. Then I set up two exceptions to catch first a file not
  • 00:04:35
    found error and second a general exception to catch any other error. Both
  • 00:04:40
    of them are written to the file error log and the console because we set up
  • 00:04:44
    the rotating file handler and the stream handler above. As we can see now an
  • 00:04:48
    example, when we run the function with a file that doesn't exist, we raise the
  • 00:04:53
    file not found error and show it in both directions. And that's it. Let's do a
  • 00:04:58
    short recap before we end this. Python's logging module keeps your debugging
  • 00:05:02
    process organized, saves critical error messages and gives you full control over
  • 00:05:07
    how and where logs are saved. If you found this helpful, please like, make
  • 00:05:12
    sure you're subscribed and check out the video YouTube suggests for you on the
  • 00:05:16
    left for more Python tips. Thanks for watching and happy coding.
标签
  • Python
  • Logging
  • Debugging
  • RotatingFileHandler
  • ConsoleHandler
  • Log Levels
  • Formatter
  • Error Messages
  • Handlers