Logger From Dictionary

Logging Inside Python Austin Cepalia 02:14

In this lesson, you’ll see how to do what you did in the last lesson, but this time, but with a dictionary approach. The most straightforward way to do this is with a YAML file for your configuration. Here’s the same configuration in a YAML format for the dictionary approach:

YAML
      
    
version: 1
formatters:
  simple:
    format: '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
handlers:
  console:
    class: logging.StreamHandler
    level: DEBUG
    formatter: simple
    stream: ext://sys.stdout
loggers:
  sampleLogger:
    level: DEBUG
    handlers: [console]
    propagate: no
root:
  level: DEBUG
  handlers: [console]

Here’s an example that shows how to load config from a yaml file:

Python
      
    
import logging
import logging.config
import yaml

with open('config.yaml', 'r') as f:
    config = yaml.safe_load(f.read())
    logging.config.dictConfig(config)

logger = logging.getLogger(__name__)

logger.debug('This is a debug message')

Here’s what you’d get:

Shell

2018-07-13 14:05:03,766 - __main__ - DEBUG - This is a debug message

00:00 Let’s do the same thing, but with a dictionary approach. The easiest way to do this is by using a YAML file for our configuration. This works in a similar way as in the last video. First, we define a new formatter called simple, and we will supply it this formatting string right here.

00:21 Then we create a new handler called console, which will use the StreamHandler class and the stdout stream, a level of DEBUG, and the simple formatter we just defined.

00:33 Then we create a logger called sampleLogger with a level of DEBUG, handlers of [console], and no for propagation. Finally, we define the root logger with a level of DEBUG and the same console handler.

00:50 This file right here is saved as config.yaml.

00:55 I’ll jump into a new Python file and start coding the mechanism for creating our logger from this YAML file. I need to import three modules this time, logging, logging.config, and yaml.

01:09 If you don’t have yaml, you can grab it by running pip install PyYAML in a command line. Now, I can open this file in the standard Python way, with open('config.yaml') in read mode ('r') as f:. I’ll read the lines with config = yaml.safe_load(f.read()).

01:37 And now I’ll configure the logger with logging.config.dictConfig(), passing in the config information. I’ll create a new logger by typing logger = logging.getLogger(__name__).

01:54 I’ll use this logger by writing logger.debug(), passing in 'This is a debug message'.

02:03 And as usual, I will right-click here and choose Run Code, and we see that we get the exact same log output as in the last video.

Olya on April 27, 2021

Austin hello,

I have reviewed your course and have attention to implement assertion for logger, could it be used for existed logs?

Thank you in advance!

Olha

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