# -*- coding: UTF-8 no BOM -*-

import os
import sys
import h5py
import numpy as np
import xml.etree.cElementTree as ET

# ---------------------------------------------------------------- #
# python 3 has no unicode object, this ensures that the code works #
# on Python 2&3                                                    #
# ---------------------------------------------------------------- #
try:
  test=isinstance('test', unicode)
except(NameError):
  unicode=str


# ------------------------------------------------------- #
# Singleton class for converting feature name to H5F path #
# ------------------------------------------------------- #
# NOTE:
#   use simple function to mimic the singleton class in
#   C++/Java
def lables_to_path(label, dsXMLPath=None):
    """ read the xml definition file and return the path."""
    if dsXMLPath is None:
        dsXMLPath = os.path.abspath(__file__).replace("h5table.py",
                                                      "DS_HDF5.xml")
    tree = ET.parse(dsXMLPath)
    dataType = tree.find('{}/type'.format(label)).text
    h5path = tree.find('{}/h5path'.format(label)).text
    return (dataType, h5path)


# ----------------------- #
# H5Table interface class #
# ----------------------- #
class H5Table(object):
    """
    DESCRIPTION
    -----------
        Interface class for manipulating data in HDF5 with DAMASK
        specialized data structure.
    PARAMETERS
    ----------
    h5f_path: str
        Absolute path the HDF5 file
    METHOD
    ------
    del_entry()
    get_attr()
    add_attr()
    get_data()
    add_data()
    NOTE
    ----
        1. As an interface class, it uses the lazy evaluation design
        that read the data only when its absolutely necessary.
        2. The command line used to generate new feature is stored with
        each dataset as dataset attribute.
    """

    def __init__(self, h5f_path):
        """
        """
        self.h5f_path = h5f_path

    def del_entry(self, feature_name):
        """ delete entry in HDF5 table """
        dataType, h5f_path = lables_to_path(feature_name)
        h5f = h5py.File(self.h5f_path, 'a')
        del h5f[h5f_path]

    def get_attr(self, attr_name):
        h5f = h5py.File(self.h5f_path, 'r')
        dataType, h5f_path = lables_to_path(attr_name)
        return h5f[h5f_path].attrs[attr_name]

    def add_attr(self, attr_name, attr_data):
        h5f = h5py.File(self.h5f_path, 'a')
        dataType, h5f_path = lables_to_path(attr_name)
        if dataType == "attr":
            h5f[h5f_path].attrs[attr_name] = attr_data
        else:
            raise ValueError("Unspported attr: {}".format(attr_name))

    def get_data(self, feature_name=None):
        """ extract dataset from HDF5 table and return it in a numpy array """
        dataType, h5f_path = lables_to_path(feature_name)
        h5f = h5py.File(self.h5f_path, 'r')
        h5f_dst = h5f[h5f_path]  # get the handle for target dataset(table)
        return h5f_dst.read_direct(np.zeros(h5f_dst.shape))

    def add_data(self, feature_name, dataset=None):
        """ adding new feature into existing HDF5 file """
        dataType, h5f_path = lables_to_path(feature_name)
        if dataType is not "attr":
            h5f = h5py.File(self.h5f_path, 'a')
            h5f.create_dataset(h5f_path, data=dataset)
        else:
            raise ValueError("feature {} isn't valid".format(feature_name))

    def get_log(self, feature_name):
        """ get cmd history used to generate the data"""
        dataType, h5f_path = lables_to_path(feature_name)
        h5f = ht5py.File(self.h5f_path, 'r')
        return h5f[h5f_path].attrs['log']