# Path: percept/utils/input.py
# def import_from_string(import_string):
#     """
#     Import a class from a string
#     import_string - string path to module to import using dot notation (foo.bar)
#     """
#     import_split = import_string.split(".")
#     import_class = import_split[-1]
#     module_path = ".".join(import_split[:-1])
#     mod = __import__(module_path, fromlist=[import_class])
#     klass = getattr(mod, import_class)
#     return klass
# 
# class DataFormats(object):
#     """
#     Define acceptable data formats
#     """
#     csv = "csv"
#     dataframe = "dataframe"
# 
# Path: percept/utils/models.py
# def find_needed_formatter(input_format, output_format):
#     """
#     Find a data formatter given an input and output format
#     input_format - needed input format.  see utils.input.dataformats
#     output_format - needed output format.  see utils.input.dataformats
#     """
#     #Only take the formatters in the registry
#     selected_registry = [re.cls for re in registry if re.category==RegistryCategories.formatters]
#     needed_formatters = []
#     for formatter in selected_registry:
#         #Initialize the formatter (needed so it can discover its formats)
#         formatter_inst = formatter()
#         if input_format in formatter_inst.input_formats and output_format in formatter_inst.output_formats:
#             needed_formatters.append(formatter)
#     if len(needed_formatters)>0:
#         return needed_formatters[0]
#     return None
# 
# def find_needed_input(input_format):
#     """
#     Find a needed input class
#     input_format - needed input format, see utils.input.dataformats
#     """
#     needed_inputs = [re.cls for re in registry if re.category==RegistryCategories.inputs and re.cls.input_format == input_format]
#     if len(needed_inputs)>0:
#         return needed_inputs[0]
#     return None
# 
# class RegistryCategories(object):
#     """
#     Define valid registry categories
#     """
#     base = "base"
#     preprocessors = "preprocessors"
#     inputs = "inputs"
#     formatters = "formatters"
#     algorithms = "algorithms"
#     workflows = "workflows"
# 
# class MetaFieldModel(type):
#     """
#     Metaclass to facilitate registration of modules
#     """
#     def __new__(cls, clsname, bases, attrs):
#         newclass = super(cls, MetaFieldModel).__new__(cls, clsname, bases, attrs)
#         newclass.name = newclass.__name__.lower()
#         register(newclass)
#         return newclass
# 
# def get_task_name(obj):
#     try:
#         name = "{0}.{1}.{2}".format(obj.category, obj.namespace, obj.name)
#     except AttributeError:
#         name = obj.__class__.__name__
# 
#     return name
# 
# def get_namespace(mod):
#     return mod.split('.')[0]
# 
# Path: percept/conf/base.py
# class Settings(object):
#     def _initialize(self, settings_module):
#     def _setup(self):
#     def __getattr__(self, name):
#     def _configure_logging(self):
#     def configured(self):
# 
# Path: percept/tests/framework.py
# class NaiveWorkflowTester(Tester):
#     test_case_format = {'config_file' : basestring}
# 
#     def test(self, **kwargs):
#         super(NaiveWorkflowTester, self).test(**kwargs)
#         config_file = kwargs.get('config_file')
# 
#         from percept.utils.workflow import WorkflowWrapper
#         wrapper = WorkflowWrapper(config_file, self.cls)
#         wrapper.run()
# 
#         assert wrapper.workflow.setup_run == True


from percept.utils.input import import_from_string, DataFormats
from percept.utils.models import find_needed_formatter, find_needed_input, RegistryCategories, MetaFieldModel, get_task_name, get_namespace
from collections import namedtuple
from percept.conf.base import settings
from percept.tests.framework import NaiveWorkflowTester
import logging
import os
                }
            )
        return reformatted_predict

    def reformat_input(self, **kwargs):
        """
        Reformat input data
        """
        reformatted_input = {}
        needed_formats = []
        for task_cls in self.tasks:
            needed_formats.append(task_cls.data_format)
        self.needed_formats = list(set(needed_formats))

        for output_format in self.needed_formats:
            reformatted_input.update(
                {
                    output_format :
                        {
                        'data' : self.reformat_file(self.input_file, self.input_format, output_format),
                        'target' : self.reformat_file(self.target_file, self.target_format, output_format)
                        }
                }
            )
        return reformatted_input

class NaiveWorkflow(BaseWorkflow):
    """
    Naive workflow that doesn't optimize anything
    """

# Path: percept/utils/input.py
# def import_from_string(import_string):
#     """
#     Import a class from a string
#     import_string - string path to module to import using dot notation (foo.bar)
#     """
#     import_split = import_string.split(".")
#     import_class = import_split[-1]
#     module_path = ".".join(import_split[:-1])
#     mod = __import__(module_path, fromlist=[import_class])
#     klass = getattr(mod, import_class)
#     return klass
# 
# class DataFormats(object):
#     """
#     Define acceptable data formats
#     """
#     csv = "csv"
#     dataframe = "dataframe"
# 
# Path: percept/utils/models.py
# def find_needed_formatter(input_format, output_format):
#     """
#     Find a data formatter given an input and output format
#     input_format - needed input format.  see utils.input.dataformats
#     output_format - needed output format.  see utils.input.dataformats
#     """
#     #Only take the formatters in the registry
#     selected_registry = [re.cls for re in registry if re.category==RegistryCategories.formatters]
#     needed_formatters = []
#     for formatter in selected_registry:
#         #Initialize the formatter (needed so it can discover its formats)
#         formatter_inst = formatter()
#         if input_format in formatter_inst.input_formats and output_format in formatter_inst.output_formats:
#             needed_formatters.append(formatter)
#     if len(needed_formatters)>0:
#         return needed_formatters[0]
#     return None
# 
# def find_needed_input(input_format):
#     """
#     Find a needed input class
#     input_format - needed input format, see utils.input.dataformats
#     """
#     needed_inputs = [re.cls for re in registry if re.category==RegistryCategories.inputs and re.cls.input_format == input_format]
#     if len(needed_inputs)>0:
#         return needed_inputs[0]
#     return None
# 
# class RegistryCategories(object):
#     """
#     Define valid registry categories
#     """
#     base = "base"
#     preprocessors = "preprocessors"
#     inputs = "inputs"
#     formatters = "formatters"
#     algorithms = "algorithms"
#     workflows = "workflows"
# 
# class MetaFieldModel(type):
#     """
#     Metaclass to facilitate registration of modules
#     """
#     def __new__(cls, clsname, bases, attrs):
#         newclass = super(cls, MetaFieldModel).__new__(cls, clsname, bases, attrs)
#         newclass.name = newclass.__name__.lower()
#         register(newclass)
#         return newclass
# 
# def get_task_name(obj):
#     try:
#         name = "{0}.{1}.{2}".format(obj.category, obj.namespace, obj.name)
#     except AttributeError:
#         name = obj.__class__.__name__
# 
#     return name
# 
# def get_namespace(mod):
#     return mod.split('.')[0]
# 
# Path: percept/conf/base.py
# class Settings(object):
#     def _initialize(self, settings_module):
#     def _setup(self):
#     def __getattr__(self, name):
#     def _configure_logging(self):
#     def configured(self):
# 
# Path: percept/tests/framework.py
# class NaiveWorkflowTester(Tester):
#     test_case_format = {'config_file' : basestring}
# 
#     def test(self, **kwargs):
#         super(NaiveWorkflowTester, self).test(**kwargs)
#         config_file = kwargs.get('config_file')
# 
#         from percept.utils.workflow import WorkflowWrapper
#         wrapper = WorkflowWrapper(config_file, self.cls)
#         wrapper.run()
# 
#         assert wrapper.workflow.setup_run == True


# Path: percept/workflows/base.py
from percept.utils.input import import_from_string, DataFormats
from percept.utils.models import find_needed_formatter, find_needed_input, RegistryCategories, MetaFieldModel, get_task_name, get_namespace
from collections import namedtuple
from percept.conf.base import settings
from percept.tests.framework import NaiveWorkflowTester
import logging
import os

                }
            )
        return reformatted_predict

    def reformat_input(self, **kwargs):
        """
        Reformat input data
        """
        reformatted_input = {}
        needed_formats = []
        for task_cls in self.tasks:
            needed_formats.append(task_cls.data_format)
        self.needed_formats = list(set(needed_formats))

        for output_format in self.needed_formats:
            reformatted_input.update(
                {
                    output_format :
                        {
                        'data' : self.reformat_file(self.input_file, self.input_format, output_format),
                        'target' : self.reformat_file(self.target_file, self.target_format, output_format)
                        }
                }
            )
        return reformatted_input

class NaiveWorkflow(BaseWorkflow):
    """
    Naive workflow that doesn't optimize anything
    """

    category = RegistryCategories.workflows