How to use the daiquiri.formatter function in daiquiri

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github garaud / jitenshea / jitenshea / __init__.py View on Github external
"""Jitenshea package

Bicycle-sharing analysis
"""

import os
import logging
import configparser

import daiquiri
import daiquiri.formatter


FORMAT = '%(asctime)s :: %(color)s%(levelname)s :: %(name)s :: %(funcName)s : %(message)s%(color_stop)s'
daiquiri.setup(level=logging.INFO, outputs=(
    daiquiri.output.Stream(formatter=daiquiri.formatter.ColorFormatter(
        fmt=FORMAT)),
    ))
logger = daiquiri.getLogger("root")


_ROOT = os.path.dirname(os.path.abspath(__file__))
_CONFIG = os.getenv('JITENSHEA_CONFIG')
_CONFIG = _CONFIG if _CONFIG is not None else os.path.join(_ROOT, 'config.ini')


if not os.path.isfile(_CONFIG):
    logger.error("Configuration file '%s' not found", _CONFIG)
    config = None
else:
    config = configparser.ConfigParser(allow_no_value=True)
    with open(_CONFIG) as fobj:
github jd / daiquiri / examples / formatter.py View on Github external
import logging

import daiquiri
import daiquiri.formatter

daiquiri.setup(level=logging.INFO, outputs=(
    daiquiri.output.Stream(formatter=daiquiri.formatter.ColorFormatter(
        fmt="%(asctime)s [PID %(process)d] [%(levelname)s] "
        "%(name)s -> %(message)s")),
    ))

logger = daiquiri.getLogger(__name__)
logger.info("It works with a custom format!")
github Oslandia / deeposlandia / deeposlandia / __init__.py View on Github external
import os

import daiquiri

__version__ = "0.6.3.post1"


# Do not log Tensorflow messages
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

# Configure the logger
daiquiri.setup(
    level=logging.INFO,
    outputs=(
        daiquiri.output.Stream(
            formatter=daiquiri.formatter.ColorFormatter(
                fmt=(
                    "%(asctime)s :: %(levelname)s :: %(module)s :: "
                    "%(funcName)s : %(color)s%(message)s%(color_stop)s"
                )
            )
        ),
    ),
)
logger = daiquiri.getLogger("root")

# Deeposlandia supports feature detection (featdet) and semantic segmentation (semseg)
AVAILABLE_MODELS = ("featdet", "semseg")

# Configuration file handling
_DEEPOSL_CONFIG = os.getenv("DEEPOSL_CONFIG")
_DEEPOSL_CONFIG = (
github jd / pifpaf / pifpaf / __main__.py View on Github external
def main(ctx, verbose=False, debug=False, log_file=None,
         env_prefix=None, global_urls_variable=None):
    formatter = daiquiri.formatter.ColorFormatter(
        fmt="%(color)s%(levelname)s "
        "[%(name)s] %(message)s%(color_stop)s")

    outputs = [
        daiquiri.output.Stream(sys.stderr, formatter=formatter)
    ]

    if log_file:
        outputs.append(daiquiri.output.File(log_file,
                                            formatter=formatter))

    ctx.obj = {
        "debug": debug,
    }
    if env_prefix is not None:
        ctx.obj['env_prefix'] = env_prefix
github sileht / pastamaker / pastamaker / utils.py View on Github external
def setup_logging():
    daiquiri.setup(
        outputs=[daiquiri.output.Stream(
            sys.stdout,
            formatter=daiquiri.formatter.ColorFormatter(
                "%(asctime)s [%(process)d] %(color)s%(levelname)-8.8s "
                "%(name)s: %(message)s%(color_stop)s"),
        )],
        level=(logging.DEBUG if config.DEBUG else logging.INFO),
    )
    daiquiri.set_default_log_levels([
        ("rq", "ERROR"),
        # ("github.Requester", "DEBUG"),
github CermakM / jupyter-require / jupyter_require / __init__.py View on Github external
from IPython import get_ipython

daiquiri.setup(
    level=logging.DEBUG,
    outputs=[
        daiquiri.output.File(
            level=logging.DEBUG,
            filename='.log',
            formatter=daiquiri.formatter.ColorFormatter(
                fmt="%(asctime)s [%(process)d] %(color)s%(levelname)-8.8s %(name)s:"
                    "%(lineno)d: [JupyterRequire] %(message)s%(color_stop)s"
            )),
        daiquiri.output.Stream(
            level=logging.WARN,
            formatter=daiquiri.formatter.ColorFormatter(
                fmt="%(asctime)s [%(process)d] %(color)s%(levelname)-8.8s %(name)s:"
                    "%(lineno)d: [JupyterRequire] %(message)s%(color_stop)s"
            )
        ),
    ],
)

logger = daiquiri.getLogger()


def load_ipython_extension(ipython):
    """Load the IPython Jupyter Require extension."""
    from .magic import RequireJSMagic

    logger.debug("Loading Jupyter Require extension.")
github jd / daiquiri / examples / extra.py View on Github external
import logging

import daiquiri
import daiquiri.formatter

daiquiri.setup(level=logging.INFO, outputs=(
    daiquiri.output.Stream(formatter=daiquiri.formatter.ColorFormatter(
        fmt=(daiquiri.formatter.DEFAULT_FORMAT +
             " [%(subsystem)s is %(mood)s]"))),
    ))

logger = daiquiri.getLogger(__name__, subsystem="example")
logger.info("It works and log to stderr by default with color!",
            mood="happy")
github IBM / matrix-capsules-with-em-routing / config.py View on Github external
def setup_logger(logger_dir, name="logger"):
  os.environ['TZ'] = 'Africa/Johannesburg'
  time.tzset()
  daiquiri_formatter = daiquiri.formatter.ColorFormatter(
      fmt= "%(asctime)s %(color)s%(levelname)s: %(message)s%(color_stop)s",
      datefmt="%Y-%m-%d %H:%M:%S")
  logger_path = os.path.join(logger_dir, name)
  daiquiri.setup(level=logging.INFO, outputs=(
      daiquiri.output.Stream(formatter=daiquiri_formatter),
      daiquiri.output.File(logger_path,formatter=daiquiri_formatter),
     ))