Skip to main content

Logger helper functions

Project description

Logging for Data Pipelines

This library simplifies the logging setup process for new data pipelines, eliminating the need to repeatedly look up logger configurations.

Installation

Install the library via pip:

pip install log4data

Usage

To start using the library, simply import it in your script, and use the default configuration if you don't want to manually configure the logger.

import src.log4data.main as l4d
import logging as lg


if __name__ == "__main__":
    l4d.default_setup_logger()
    lg.info("Setup complete")

With just a few lines of code, you can set up effective logging. This will generate a log like this:

2024-07-03 00:00:00,000 - root - INFO - We are logging!

A more advanced use of the library is parametrize the file name or the logging level like this:

# main.py
import log4data as l4d
import logging as lg


if __name__ == "__main__":
    args = l4d.set_log_args(return_args=True)
    l4d.setup_logger(args)

    lg.info("Setup complete")

And then call python:

python main.py -lglv debug -lgfn etl.log

Finally, @inject_logger is a decorator to automatically add a logger to a function, named after that function. This is used like this:

# main.py
import argparse
import logging as lg
import log4data as l4d


@l4d.inject_logger
def my_data_processing_function(data, logger=None):
    logger.info(f"Processing data: {data}")
    print(data)
    return data


if __name__ == "__main__":
    # parse arguments
    parser = argparse.ArgumentParser()
    parser.add_argument("-d", "--data", type=str, default="sample data")
    l4d.set_log_args(parser)
    args = parser.parse_args()

    # Configure logging
    l4d.setup_logger(args)

    # Call the function without providing the logger manually
    my_data_processing_function(args.data)

Then, calling this:

python main.py -d "Hello log for data."

Results in this log:

2024-07-03 00:00:00,000 - my_data_processing_function - INFO - Processing data: Hello log for data.

Contributing

This is a small project developed for my team and me, and while major upgrades are not planned, we welcome pull requests. If you encounter bugs or wish to suggest new features, please initiate a discussion by opening an issue.

License

This repository is under the MIT license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

log4data-0.1.0.tar.gz (4.8 kB view details)

Uploaded Source

Built Distribution

log4data-0.1.0-py3-none-any.whl (5.1 kB view details)

Uploaded Python 3

File details

Details for the file log4data-0.1.0.tar.gz.

File metadata

  • Download URL: log4data-0.1.0.tar.gz
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for log4data-0.1.0.tar.gz
Algorithm Hash digest
SHA256 9553236d13e32b651bc33245469045aec00ef2d65b41d1340376faec98c2bd5c
MD5 5b8ffa29a22c5c1c0c7fa328c7c48340
BLAKE2b-256 02cb1740964504b553dcb4e56f06f250f2bef7c42c9eff071b7c9f7aab3a9dcb

See more details on using hashes here.

File details

Details for the file log4data-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: log4data-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 5.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for log4data-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 77acd4378085f975c4a9deeb4dd1730ae0221d431ec6c0337d7dc588a722ca75
MD5 3379d7222d51c0ca3890fc6b6803687d
BLAKE2b-256 4396a180179b631f485f85e204ba5e7ca9c7530d527793abe43a451ffc268171

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page