# Copyright 2018 Artem Artemev @awav
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


from datetime import datetime

import h5py
import numpy as np
import tensorflow as tf

from .coders import CoderDispatcher
from .context import BaseContext
from .serializers import HDF5Serializer


class SaverContext(BaseContext):
    def __init__(self, version=None, serializer=None, **kwargs):
        super().__init__(**kwargs)
        self.serializer = HDF5Serializer if serializer is None else serializer


class Saver:
    def save(self, pathname, target, context=None):
        context = Saver.__get_context(context)
        encoded_target = CoderDispatcher(context).encode(target)
        context.serializer(context).dump(pathname, encoded_target)

    def load(self, pathname, context=None):
        context = Saver.__get_context(context)
        encoded_target = context.serializer(context).load(pathname)
        return CoderDispatcher(context).decode(encoded_target)

    @staticmethod
    def __get_context(context):
        if context is None:
            context = SaverContext()
        if not isinstance(context, SaverContext):
            raise ValueError('The context must be instance of "SaverContext" class.')
        return context