from .DataStream import DataReadStream,open_hdf5
from .DataStream import ENetPosmap as pos_map

import numpy as np
import re
from collections import defaultdict
import time as time

__all__ = ['NetchkReader']

import logging
log = logging.getLogger('reader')

class NetchkReader(DataReadStream):
    def __init__(self):
        file = '/var/www/html/data/stdata/netchk.hdf5'
        hfive = open_hdf5(file,False)
        super(NetchkReader,self).__init__(hfive)

    def __del__(self):
        self.close()
        super(NetchkReader, self).__del__()

    def tuple_path(self, day: int, chnames: set = None):
        def parse(path):
            items = re.split(r'/', path)
            (_prifix, _version, today, chname) = items
            return chname

        all = True if chnames is None or len(chnames) == 0 else False
        channels = set()
        pathes = self.datasets(day)
        for path in pathes:
            _chname = parse(path)
            if all:
                channels.add(_chname)
            elif _chname in chnames:
                channels.add(_chname)
            else:
                continue

        return channels

    def many_tuple_path(self, days: list, chnames: set = None):
        all = set()
        for day in days:
            channels = self.tuple_path(day, chnames)
            all = all.union(channels)
        return all

    def init_data(self, days):
        dim = pos_map.dim()
        return np.zeros((dim, 86400 * days))

    def read(self, today, chname):
        path = f'/{self._version}/{today}/{chname}'

        hfive = self.file
        if path in hfive:
            return hfive[path]
        else:
            return None
    pass
    pass