""" hdf5 file based storage; this modules adds the possibility to dump dict as
    hdf5 File """
import numpy as np
import os
import h5py 
import collections

import logging as log
log.basicConfig(level=log.INFO)

def dictToH5Group(d,group):
  """ helper function that transform (recursively) a dictionary into an
      hdf group """
  for key,value in d.items():
    if not isinstance(value,(dict,collections.OrderedDict)):
      # hacks for special s...
      # h5py can't handle numpy unicode arrays
      if isinstance(value,np.ndarray) and value.dtype.char == "U":
        value = np.asarray([vv.encode('ascii') for vv in value])
      # h5py can't save None
      if value is None: value="NONE_PYTHON_OBJECT"
      try:
        group[key] = value
      except TypeError:
        log.error("Can't save %s"%(key))
    else:
      group.create_group(key)
      dictToH5Group(value,group[key])

def dictToH5(h5,d):
  """ Save a dictionary into an hdf5 file
      h5py is not capable of handling dictionaries natively"""
  h5 = h5py.File(h5,mode="w")
#  group = h5.create_group("/")
  dictToH5Group(d,h5["/"])
  h5.close()

def h5dataToDict(h5):
  """ Read a hdf5 group into a dictionary """
  if isinstance(h5,h5py.Dataset):
    temp = h5[...]
    # hack for special s...
    # unwrap 0d arrays
    if isinstance(temp,np.ndarray) and temp.ndim == 0:
      temp=temp.item()
      # h5py can't handle None
      if temp == "NONE_PYTHON_OBJECT": temp=None
    # convert back from ascii to unicode
    if isinstance(temp,np.ndarray) and temp.dtype.char == "S":
      temp = temp.astype(str)
    return temp
  else:
    ret = dict()
    for k,v in h5.items(): ret[k] = h5dataToDict(v)
    return ret

def h5ToDict(h5):
  """ Read a hdf5 file into a dictionary """
  with h5py.File(h5,"r") as h:
    ret = h5dataToDict( h["/"] )
  return ret


def npzToDict(npzFile):
  with np.load(npzFile) as npz: d = dict(npz)
  # unwrap 0d arrays
  for key,value in d.items():
    if isinstance(value,np.ndarray) and value.ndim == 0: d[key]=value.item()
  return d

def dictToNpz(npzFile,d): np.savez(npzFile,**d)

def read(fname):
  extension = os.path.splitext(fname)[1]
  log.info("Reading storage file %s"%fname)
  if extension == ".npz": 
    return npzToDict(fname)
  elif extension == ".h5":
    return h5ToDict(fname)
  else:
    raise ValueError("Extension must be h5 or npz, it was %s"%extension) 

def save(fname,d):
  extension = os.path.splitext(fname)[1]
  log.info("Saving storage file %s"%fname)
  if extension == ".npz": 
    return dictToNpz(fname,d)
  elif extension == ".h5":
    return dictToH5(fname,d)
  else:
    raise ValueError("Extension must be h5 or npz")