# Path: dftimewolf/config.py
# class Config(object):
#   def GetExtra(cls, name: str='') -> Dict[str, Any]:
#   def LoadExtra(cls, filename: str) -> bool:
#   def LoadExtraData(cls, json_string: bytes) -> None:
#   def ClearExtra(cls) -> None:
# 
# Path: dftimewolf/lib/state.py
# T = TypeVar("T", bound="interface.AttributeContainer")  # pylint: disable=invalid-name,line-too-long
# NEW_ISSUE_URL = 'https://github.com/log2timeline/dftimewolf/issues/new'
# class DFTimewolfState(object):
#   def __init__(self, config: Type[Config]) -> None:
#   def _InvokeModulesInThreads(self, callback: Callable[[Any], Any]) -> None:
#   def ImportRecipeModules(self, module_locations: Dict[str, str]) -> None:
#   def LoadRecipe(self,
#                  recipe: Dict[str, Any],
#                  module_locations: Dict[str, str]) -> None:
#   def FormatExecutionPlan(self) -> str:
#   def LogExecutionPlan(self) -> None:
#   def AddToCache(self, name: str, value: Any) -> None:
#   def GetFromCache(self, name: str, default_value: Any=None) -> Any:
#   def StoreContainer(self, container: "interface.AttributeContainer") -> None:
#   def GetContainers(self,
#                     container_class: Type[T],
#                     pop: bool=False) -> Sequence[T]:
#   def DedupeContainers(self, container_class: Type[T]) -> None:
#   def _SetupModuleThread(self, module_definition: Dict[str, str]) -> None:
#   def SetupModules(self) -> None:
#   def _RunModuleThread(self, module_definition: Dict[str, str]) -> None:
#   def RunPreflights(self) -> None:
#   def CleanUpPreflights(self) -> None:
#   def InstantiateModule(self, module_name: str) -> "dftw_module.BaseModule":
#   def RunModules(self) -> None:
#   def RegisterStreamingCallback(
#       self,
#       target: Callable[["interface.AttributeContainer"], Any],
#       container_type: Type["interface.AttributeContainer"]) -> None:
#   def StreamContainer(self, container: "interface.AttributeContainer") -> None:
#   def AddError(self, error: DFTimewolfError) -> None:
#   def CleanUp(self) -> None:
#   def CheckErrors(self, is_global: bool=False) -> None:
# 
# Path: dftimewolf/lib/timesketch_utils.py
# LOCK = threading.Lock()
# def GetApiClient(state: "state.DFTimewolfState",
#                  token_password: str='') -> client.TimesketchApi:


import unittest
from dftimewolf import config
from dftimewolf.lib import state
from dftimewolf.lib import timesketch_utils
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests timesketch utilities."""



class FakeTimesketchApiClient(object):
  """Fake API Client Class."""
  TYPE = 'client'


class TimesketchUtilsTest(unittest.TestCase):
  """Tests for the Timesketch utils."""

  def testInitialization(self):
    """Tests that the processor can be initialized."""
    wolf_config = config.Config()
    wolf_state = state.DFTimewolfState(wolf_config)
    wolf_state.AddToCache('timesketch_client', FakeTimesketchApiClient())


# Path: dftimewolf/config.py
# class Config(object):
#   def GetExtra(cls, name: str='') -> Dict[str, Any]:
#   def LoadExtra(cls, filename: str) -> bool:
#   def LoadExtraData(cls, json_string: bytes) -> None:
#   def ClearExtra(cls) -> None:
# 
# Path: dftimewolf/lib/state.py
# T = TypeVar("T", bound="interface.AttributeContainer")  # pylint: disable=invalid-name,line-too-long
# NEW_ISSUE_URL = 'https://github.com/log2timeline/dftimewolf/issues/new'
# class DFTimewolfState(object):
#   def __init__(self, config: Type[Config]) -> None:
#   def _InvokeModulesInThreads(self, callback: Callable[[Any], Any]) -> None:
#   def ImportRecipeModules(self, module_locations: Dict[str, str]) -> None:
#   def LoadRecipe(self,
#                  recipe: Dict[str, Any],
#                  module_locations: Dict[str, str]) -> None:
#   def FormatExecutionPlan(self) -> str:
#   def LogExecutionPlan(self) -> None:
#   def AddToCache(self, name: str, value: Any) -> None:
#   def GetFromCache(self, name: str, default_value: Any=None) -> Any:
#   def StoreContainer(self, container: "interface.AttributeContainer") -> None:
#   def GetContainers(self,
#                     container_class: Type[T],
#                     pop: bool=False) -> Sequence[T]:
#   def DedupeContainers(self, container_class: Type[T]) -> None:
#   def _SetupModuleThread(self, module_definition: Dict[str, str]) -> None:
#   def SetupModules(self) -> None:
#   def _RunModuleThread(self, module_definition: Dict[str, str]) -> None:
#   def RunPreflights(self) -> None:
#   def CleanUpPreflights(self) -> None:
#   def InstantiateModule(self, module_name: str) -> "dftw_module.BaseModule":
#   def RunModules(self) -> None:
#   def RegisterStreamingCallback(
#       self,
#       target: Callable[["interface.AttributeContainer"], Any],
#       container_type: Type["interface.AttributeContainer"]) -> None:
#   def StreamContainer(self, container: "interface.AttributeContainer") -> None:
#   def AddError(self, error: DFTimewolfError) -> None:
#   def CleanUp(self) -> None:
#   def CheckErrors(self, is_global: bool=False) -> None:
# 
# Path: dftimewolf/lib/timesketch_utils.py
# LOCK = threading.Lock()
# def GetApiClient(state: "state.DFTimewolfState",
#                  token_password: str='') -> client.TimesketchApi:


# Path: tests/lib/timesketch_utils.py
import unittest
from dftimewolf import config
from dftimewolf.lib import state
from dftimewolf.lib import timesketch_utils

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests timesketch utilities."""



class FakeTimesketchApiClient(object):
  """Fake API Client Class."""
  TYPE = 'client'


class TimesketchUtilsTest(unittest.TestCase):
  """Tests for the Timesketch utils."""

  def testInitialization(self):
    """Tests that the processor can be initialized."""
    wolf_config = config.Config()
    wolf_state = state.DFTimewolfState(wolf_config)
    wolf_state.AddToCache('timesketch_client', FakeTimesketchApiClient())


    timesketch_client = timesketch_utils.GetApiClient(wolf_state)