https://github.com/waikato-datamining/wai-logging
Simple helper library for logging.
https://github.com/waikato-datamining/wai-logging
logging python3
Last synced: 3 months ago
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Simple helper library for logging.
- Host: GitHub
- URL: https://github.com/waikato-datamining/wai-logging
- Owner: waikato-datamining
- License: mit
- Created: 2023-11-29T22:49:56.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-13T20:47:47.000Z (6 months ago)
- Last Synced: 2025-03-22T15:48:26.092Z (4 months ago)
- Topics: logging, python3
- Language: Python
- Homepage:
- Size: 15.6 KB
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGES.rst
- License: LICENSE
Awesome Lists containing this project
README
# wai-logging
Simple helper library for logging.
## Installation
From PyPI:
```bash
pip install wai_logging
```
From Github:
```bash
pip install git+https://github.com/waikato-datamining/wai-logging.git
```
## Methods
The following helper methods are available:
* `init_logging` - initializes the logging with a default level, which can be overridden with an environment variable
* `set_logging_level` - sets the logging level of a `logging.Logger` instance
* `str_to_logging_level` - turns a string logging level into a `logging` module one, used by `init_logging` and `set_logging_level`
* `add_logging_level` - adds an option for the logging level to an `argparse.ArgumentParser` instance
* `add_logger_name` - adds an option for a custom name for a logger to an `argparse.ArgumentParser` instance
## Usage
Below are some examples on how to use the aforementioned methods and what the
output may look like.
### Example 1
The following logging setup only outputs on stderr using a simple format without timestamps:
```python
from wai.logging import init_logging, LOGGING_INFO, set_logging_level
import logging
init_logging(LOGGING_INFO)
logger = logging.getLogger("my.test")
set_logging_level(logger, LOGGING_INFO)
logger.debug("debugging output")
logger.info("info output")
logger.warning("warning output")
```
The output:
```
INFO:my.test:info output
WARNING:my.test:warning output
```
### Example 2
This configuration uses timestamps in its output (`log_format`; see [format strings](https://docs.python.org/3/library/logging.html#logrecord-attributes))
and logs to a file as well (`filename`):
```python
from wai.logging import init_logging, LOGGING_INFO, set_logging_level, TIMESTAMP_LOG_FORMAT
import logging
init_logging(LOGGING_INFO, filename="./out.log", log_format=TIMESTAMP_LOG_FORMAT)
logger = logging.getLogger("my.test")
set_logging_level(logger, LOGGING_INFO)
logger.debug("debugging output")
logger.info("info output")
logger.warning("warning output")
```
The output:
```
2025-01-14 09:25:22,837 - INFO - my.test - info output
2025-01-14 09:25:22,837 - WARNING - my.test - warning output
```
### Example 3
The following setup uses a [rotating file handler](https://docs.python.org/3/library/logging.handlers.html#logging.handlers.RotatingFileHandler)
and keeps a maximum of three backups (`backupCount`; log files get a numeric suffix like `.1`).
A rotation is initiated when the process is restarted and the log file exceeds 100 bytes (`maxBytes`).
```python
from wai.logging import init_logging, LOGGING_INFO, set_logging_level
import logging.handlers
init_logging(LOGGING_INFO, handlers=[
logging.StreamHandler(),
logging.handlers.RotatingFileHandler(filename="./out.log", backupCount=3, maxBytes=100)])
logger = logging.getLogger("my.test")
set_logging_level(logger, LOGGING_INFO)
logger.debug("debugging output")
logger.info("info output")
logger.warning("warning output")
```
The output:
```
INFO:my.test:info output
WARNING:my.test:warning output
```