Logging

Logging is used throughout dgraphpandas using the standard logging module.

Command Line

If you are using the command line tool then setting the logging level is as simple as passing an additional parameter.

dgraphpandas -v DEBUG

Where the following levels are supported: DEBUG,INFO,WARNING,ERROR,NOTSET

Coloring Logs

By default these will log to stdout with no color but you can also add coloring by installing the coloredlogs module 🌈.

python -m pip install coloredlogs

Environment Variables

The logging level can also be set via environment variable:

export DGRAPHPANDAS_LOG=DEBUG

Module

If you are using dgraphpandas in your own script then you can set logging on a more granular level like so:

import logging
import dgraphpandas as dpd

logging.basicConfig()
logging.getLogger('dgraphpandas.rdf').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.types').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.config').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.strategies.horizontal').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.strategies.vertical').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.strategies.vertical_helpers').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.strategies.schema').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.writers.upserts').setLevel(logging.DEBUG)
logging.getLogger('dgraphpandas.writers.schema').setLevel(logging.DEBUG)

# your logic
dpd.to_rdf('input.csv', config, 'config_key')

Naturally this means that you can redirect logs to any handler you would like:

logging_file = 'dgraphpandas.log'

logging.basicConfig()
rdf_logger = logging.getLogger('dgraphpandas.rdf')
rdf_logger.setLevel(logging.DEBUG)

# Create and add any Handler
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
file_handler = logging.FileHandler(logging_file)
file_handler.setFormatter(formatter)

rdf_logger.addHandler(file_handler)