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How to Ignore Logging for Specific Modules in Python

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Discover how to effectively filter logging in Python to exclude specific modules like `paramiko` while retaining logs from others.
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Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Ignore logging for some modules
If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
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Ignoring Logging for Specific Modules in Python
When working with Python, particularly in larger projects, logging is an invaluable tool for monitoring your application's performance and debugging issues. However, there may be instances where you might want to filter out log messages from certain libraries, such as paramiko, while still capturing logs from your own application. In this guide, we'll take a look at how to effectively ignore logging for specific modules by using the Python logging module.
The Problem
Imagine you have a Python application that utilizes the exhausted module, which includes paramiko, a library for SSH connections and file transfers. When you log activity using the standard logging setup, you might notice that the log file is cluttered with entries generated by paramiko, making it difficult to focus on your own application's log messages. Your goal is to keep the logs generated by your application while ignoring those coming from the paramiko library.
Here’s a snippet of the code you might have:
[[See Video to Reveal this Text or Code Snippet]]
In this setup, all log messages, including those from paramiko, are being recorded.
The Solution
To filter out logs from paramiko, you can adjust its logging level to a higher severity than you want to record. This can be done using the setLevel method of the logging module. Here’s how you can do it:
Step 1: Import the logging module
Ensure that you have already imported the logging module in your script.
Step 2: Set the logging level for paramiko
You can set the logging level of the paramiko logger to CRITICAL + 1, which effectively turns off logging for that module. Here’s how to implement it:
[[See Video to Reveal this Text or Code Snippet]]
This line of code tells the logging module to ignore any logs that have a level of CRITICAL or lower (which includes DEBUG, INFO, WARNING, and ERROR).
Step 3: Choose an appropriate level
If you still want to capture some messages from paramiko, you can set a different level, such as ERROR which will allow ERROR and CRITICAL messages through. Here’s how that would look:
[[See Video to Reveal this Text or Code Snippet]]
Full Example Code
Here’s the complete code implementing the solution:
[[See Video to Reveal this Text or Code Snippet]]
Conclusion
By utilizing the logging module's getLogger and setLevel functions, you can easily manage which log messages are recorded. This way, you can keep your project's log files clean and focused on relevant information without the noise from third-party libraries such as paramiko.
Now you can take control of your logging output and ensure that it serves you well, providing insights where needed without the clutter of unnecessary logs! Happy coding!
---
Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Ignore logging for some modules
If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Ignoring Logging for Specific Modules in Python
When working with Python, particularly in larger projects, logging is an invaluable tool for monitoring your application's performance and debugging issues. However, there may be instances where you might want to filter out log messages from certain libraries, such as paramiko, while still capturing logs from your own application. In this guide, we'll take a look at how to effectively ignore logging for specific modules by using the Python logging module.
The Problem
Imagine you have a Python application that utilizes the exhausted module, which includes paramiko, a library for SSH connections and file transfers. When you log activity using the standard logging setup, you might notice that the log file is cluttered with entries generated by paramiko, making it difficult to focus on your own application's log messages. Your goal is to keep the logs generated by your application while ignoring those coming from the paramiko library.
Here’s a snippet of the code you might have:
[[See Video to Reveal this Text or Code Snippet]]
In this setup, all log messages, including those from paramiko, are being recorded.
The Solution
To filter out logs from paramiko, you can adjust its logging level to a higher severity than you want to record. This can be done using the setLevel method of the logging module. Here’s how you can do it:
Step 1: Import the logging module
Ensure that you have already imported the logging module in your script.
Step 2: Set the logging level for paramiko
You can set the logging level of the paramiko logger to CRITICAL + 1, which effectively turns off logging for that module. Here’s how to implement it:
[[See Video to Reveal this Text or Code Snippet]]
This line of code tells the logging module to ignore any logs that have a level of CRITICAL or lower (which includes DEBUG, INFO, WARNING, and ERROR).
Step 3: Choose an appropriate level
If you still want to capture some messages from paramiko, you can set a different level, such as ERROR which will allow ERROR and CRITICAL messages through. Here’s how that would look:
[[See Video to Reveal this Text or Code Snippet]]
Full Example Code
Here’s the complete code implementing the solution:
[[See Video to Reveal this Text or Code Snippet]]
Conclusion
By utilizing the logging module's getLogger and setLevel functions, you can easily manage which log messages are recorded. This way, you can keep your project's log files clean and focused on relevant information without the noise from third-party libraries such as paramiko.
Now you can take control of your logging output and ensure that it serves you well, providing insights where needed without the clutter of unnecessary logs! Happy coding!