# Path: dftimewolf/lib/errors.py
# class DFTimewolfError(Exception):
# class BadConfigurationError(DFTimewolfError):
# class RecipeParseError(DFTimewolfError):
# class CommandLineParseError(DFTimewolfError):
# class CriticalError(DFTimewolfError):
#   def __init__(self,
#                message: Optional[str]=None,
#                name: Optional[str]=None,
#                stacktrace: Optional[str]=None,
#                critical: bool=False,
#                unexpected: bool=False) -> None:
# 
# Path: dftimewolf/lib/logging_utils.py
# def _GenerateTempLogFile() -> str:
# def _GenerateColorSequences() -> List[str]:
#   def success(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=invalid-name
#   def __init__(
#       self,
#       colorize: bool = True,
#       random_color: bool = False,
#       threaded: bool = False,
#       **kwargs: Any) -> None:
#   def format(self, record: LogRecord) -> str:
# DEFAULT_LOG_FILE = _GenerateTempLogFile()
# SUCCESS = 25  # 25 is right between INFO and WARNING
# COLOR_SEQS = _GenerateColorSequences()
# RESET_SEQ = '\u001b[0m'
# BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = COLOR_SEQS[8:16]
# BG_RED = '\u001b[41m'  # Red background
# BG_GREEN = '\u001b[42m'  # Green background
# BOLD = '\u001b[1m'  # Bold / bright modifier
# LOG_FORMAT = (
#     '[%(asctime)s] [{0:s}{color:s}%(name)-20s{1:s}] %(levelname)-8s'
#     ' %(message)s')
# LEVEL_COLOR_MAP = {
#     'WARNING': YELLOW,
#     'SUCCESS': BOLD + BG_GREEN + BLACK,
#     'INFO': WHITE,
#     'DEBUG': BLUE,
#     'CRITICAL': BOLD + BG_RED + WHITE,
#     'ERROR': RED
# }
# class WolfLogger(logging.getLoggerClass()):  # type: ignore
# class WolfFormatter(logging.Formatter):
# 
# Path: dftimewolf/lib/containers/interface.py
# class AttributeContainer():
#   CONTAINER_TYPE = None  # type: str
#   def __init__(self, attributes: Optional[List[Dict[str, Any]]] = None):
#   def GetAttributeNames(self) -> List[str]:


import abc
import logging
import traceback
import sys
from logging import handlers
from typing import Optional, TYPE_CHECKING, Type, cast, TypeVar, Dict, Any
from dftimewolf.lib import errors
from dftimewolf.lib import logging_utils
from dftimewolf.lib.containers import interface
  from dftimewolf.lib import state  # pylint: disable=cyclic-import
        random_color=True,
        threaded=threaded)
    console_handler.setFormatter(formatter)

    self.logger.addHandler(console_handler)

  def CleanUp(self) -> None:
    """Cleans up module output to prepare it for the next module."""
    # No clean up is required.
    return

  def ModuleError(self, message: str, critical: bool=False) -> None:
    """Declares a module error.

    Errors will be stored in a DFTimewolfError error object and passed on to the
    state. Critical errors will also raise a DFTimewolfError error.

    Args:
      message (str): Error text.
      critical (Optional[bool]): True if dfTimewolf cannot recover from
          the error and should abort execution.

    Raises:
      errors.DFTimewolfError: If the error is critical and dfTimewolf
          should abort execution of the recipe.
    """
    stacktrace = None
    if sys.exc_info() != (None, None, None):
      stacktrace = traceback.format_exc()


# Path: dftimewolf/lib/errors.py
# class DFTimewolfError(Exception):
# class BadConfigurationError(DFTimewolfError):
# class RecipeParseError(DFTimewolfError):
# class CommandLineParseError(DFTimewolfError):
# class CriticalError(DFTimewolfError):
#   def __init__(self,
#                message: Optional[str]=None,
#                name: Optional[str]=None,
#                stacktrace: Optional[str]=None,
#                critical: bool=False,
#                unexpected: bool=False) -> None:
# 
# Path: dftimewolf/lib/logging_utils.py
# def _GenerateTempLogFile() -> str:
# def _GenerateColorSequences() -> List[str]:
#   def success(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=invalid-name
#   def __init__(
#       self,
#       colorize: bool = True,
#       random_color: bool = False,
#       threaded: bool = False,
#       **kwargs: Any) -> None:
#   def format(self, record: LogRecord) -> str:
# DEFAULT_LOG_FILE = _GenerateTempLogFile()
# SUCCESS = 25  # 25 is right between INFO and WARNING
# COLOR_SEQS = _GenerateColorSequences()
# RESET_SEQ = '\u001b[0m'
# BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE = COLOR_SEQS[8:16]
# BG_RED = '\u001b[41m'  # Red background
# BG_GREEN = '\u001b[42m'  # Green background
# BOLD = '\u001b[1m'  # Bold / bright modifier
# LOG_FORMAT = (
#     '[%(asctime)s] [{0:s}{color:s}%(name)-20s{1:s}] %(levelname)-8s'
#     ' %(message)s')
# LEVEL_COLOR_MAP = {
#     'WARNING': YELLOW,
#     'SUCCESS': BOLD + BG_GREEN + BLACK,
#     'INFO': WHITE,
#     'DEBUG': BLUE,
#     'CRITICAL': BOLD + BG_RED + WHITE,
#     'ERROR': RED
# }
# class WolfLogger(logging.getLoggerClass()):  # type: ignore
# class WolfFormatter(logging.Formatter):
# 
# Path: dftimewolf/lib/containers/interface.py
# class AttributeContainer():
#   CONTAINER_TYPE = None  # type: str
#   def __init__(self, attributes: Optional[List[Dict[str, Any]]] = None):
#   def GetAttributeNames(self) -> List[str]:


# Path: dftimewolf/lib/module.py
import abc
import logging
import traceback
import sys
from logging import handlers
from typing import Optional, TYPE_CHECKING, Type, cast, TypeVar, Dict, Any
from dftimewolf.lib import errors
from dftimewolf.lib import logging_utils
from dftimewolf.lib.containers import interface
  from dftimewolf.lib import state  # pylint: disable=cyclic-import

        random_color=True,
        threaded=threaded)
    console_handler.setFormatter(formatter)

    self.logger.addHandler(console_handler)

  def CleanUp(self) -> None:
    """Cleans up module output to prepare it for the next module."""
    # No clean up is required.
    return

  def ModuleError(self, message: str, critical: bool=False) -> None:
    """Declares a module error.

    Errors will be stored in a DFTimewolfError error object and passed on to the
    state. Critical errors will also raise a DFTimewolfError error.

    Args:
      message (str): Error text.
      critical (Optional[bool]): True if dfTimewolf cannot recover from
          the error and should abort execution.

    Raises:
      errors.DFTimewolfError: If the error is critical and dfTimewolf
          should abort execution of the recipe.
    """
    stacktrace = None
    if sys.exc_info() != (None, None, None):
      stacktrace = traceback.format_exc()


    error = errors.DFTimewolfError(