""" npy/npz/hdf5 file based storage; 
    this modules adds the possibility to dump and load objects in files and
    a more convenient was of accessing the data via the .attributedict thanks
    to the DataStorage class """
import numpy as np
import os
import h5py 
import collections

import logging
log = logging.getLogger(__name__)  # __name__ is "foo.bar" here

def unwrapArray(a,recursive=True,readH5pyDataset=True):
  """ This function takes an object (like a dictionary) and recursively
      unwraps it solving many issues like the fact that many objects are 
      packaged as 0d array
      This funciton has also some specific hack for handling h5py limit to 
      handle for example the None object or the numpy unicode ...
  """
  # is h5py dataset convert to array
  if isinstance(a,h5py.Dataset) and readH5pyDataset: a = a[...]
  if isinstance(a,h5py.Dataset) and a.shape == (): a = a[...]
  if isinstance(a,np.ndarray)   and a.ndim  == 0 : a = a.item()
  if isinstance(a,np.ndarray)   and a.dtype.char == "S": a = a.astype(str)
  if recursive:
    if "items" in dir(a): # dict, h5py groups, npz file
      a = dict(a); # convert to dict, otherwise can't asssign values
      for key,value in a.items(): a[key] = unwrapArray(value)
    elif isinstance(a,list):
      for index in range(len(a)): a[index] = unwrapArray(a[index])
    else:
      pass
  if isinstance(a,dict): a = DataStorage(a)
  # restore None that cannot be saved in h5py
  if isinstance(a,str) and a == "NONE_PYTHON_OBJECT": a = None
  # h5py can't save numpy unicode
  if isinstance(a,np.ndarray) and a.dtype.char == "S": a = a.astype(str)
  return a

def dictToH5Group(d,group):
  """ helper function that transform (recursive) a dictionary into an
      hdf group by creating subgroups """
  for key,value in d.items():
    if isinstance(value,dict):
      group.create_group(key)
      dictToH5Group(value,group[key])
    else:
      # 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))

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

def h5ToDict(h5,readH5pyDataset=True):
  """ Read a hdf5 file into a dictionary """
  with h5py.File(h5,"r") as h:
    ret = unwrapArray(h,recursive=True,readH5pyDataset=readH5pyDataset)
  return ret

def npzToDict(npzFile):
  with np.load(npzFile) as npz: d = dict(npz)
  d = unwrapArray(d,recursive=True)
  return d

def npyToDict(npyFile):
  d = unwrapArray( np.load(npyFile).item() ,recursive=True)
  return d

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

def objToDict(o,recursive=True):
  """ convert a DictWrap to a dictionary (useful for saving); it should work for other objects too 
      TODO: this function does not catch a list of DataStorage instances like
      objToDict( ( DataStorage(), DataStorage() ) )
      is not converted !!
  """
  if "items" not in dir(o): return o 
  d = dict()
  for k,v in o.items():
    try:
      d[k] = objToDict( v )
    except Exception as e:
      log.info("In objToDict, could not convert key %s to dict, error was"%\
                (k,e))
      d[k] = v
  return d


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

def save(fname,d):
  # make sure the object is dict (recursively) this allows reading it
  # without the DataStorage module
  d = objToDict(d,recursive=True)
  d['filename'] = fname
  extension = os.path.splitext(fname)[1]
  log.info("Saving storage file %s"%fname)
  try:
    if extension == ".npz": 
      return dictToNpz(fname,d)
    elif extension == ".h5":
      return dictToH5(fname,d)
    elif extension == ".npy":
      return dictToNpy(fname,d)
    else:
      raise ValueError("Extension must be h5, npy or npz, it was %s"%extension) 
  except Exception as e:
    log.exception("Could not save %s"%fname)


class DataStorage(dict):
  """ Storage for dict like object.
      recursive : bool
         recursively convert dict-like objects to DataStorage
      It can save data to file (format npy,npz or h5)

      To initialize it:

        data = DataStorage( dict( a=(1,2,3),b="add"),filename='store.npz' )

        data = DataStorage( a=(1,2,3), b="add" )

        reads from file if it exists
        data = DataStorage( 'mysaveddata.npz' ) ;

        DOES NOT READ FROM FILE (even if it exists)!!
        data = DataStorage( filename = 'mysaveddata.npz' ); 

        create empty storage (with default filename)
        data = DataStorage()
  """
  def __init__(self,*args,filename='data_storage.npz',recursive=True,**kwargs):
#    self.filename = kwargs.pop('filename',"data_storage.npz")
    self.filename = filename
    # interpret kwargs as dict if there are
    if len(kwargs) != 0:
      fileOrDict = dict(kwargs)
    elif len(kwargs)==0 and len(args)>0:
      fileOrDict = args[0]
    else:
      fileOrDict = dict()

    d = dict(); # data dictionary
    if isinstance(fileOrDict,dict):
      d = fileOrDict
    elif isinstance(fileOrDict,str):
      if os.path.isfile(fileOrDict):
        d = read(fileOrDict)
      else:
        self.filename=fileOrDict
        d = dict()
    else:
      raise ValueError("Invalid DataStorage definition")

    if recursive:
      for k in d.keys():
        if not isinstance(d[k],DataStorage) and isinstance(d[k],dict):
          d[k] = DataStorage(d[k])

    # allow accessing with .data, .delays, etc.
    for k,v in d.items(): setattr(self,k,v)

    # allow accessing as proper dict
    self.update( **dict(d) )

  def __setitem__(self, key, value):
    #print("__setitem__")
    setattr(self,key,value)
    super().__setitem__(key, value)

  def __setattr__(self, key, value):
    """ allows to add fields with data.test=4 """
    #print("__setattr__")
    if isinstance(value,(dict,collections.OrderedDict)): value = DataStorage(value)
    super().__setitem__(key, value)
    super().__setattr__(key,value)

  def __delitem__(self, key):
    delattr(self,key)
    super().__delitem__(key)

  def __str__(self):
    keys = list(self.keys())
    keys.sort()
    return "DataStorage obj containing: %s" % ",".join(keys)

  def __repr__(self):
    keys = list(self.keys())
    keys.sort()
    if len(keys) == 0: return "Empty DataStorage"
    nchars = max(map(len,keys))
    fmt = "%%%ds %%s" % (nchars)
    s = ["DataStorage obj containing (sorted): ",]
    for k in keys:
      obj = self[k]
      if isinstance(obj,np.ndarray):
        value_str = "array, size %s, type %s"% ("x".join(map(str,obj.shape)),obj.dtype)
      elif isinstance(obj,DataStorage):
        value_str = str(obj)[:50]
      elif isinstance(obj,(str,DataStorage)):
        value_str = obj[:50] 
      elif isinstance(obj,(list,tuple)) and all( [isinstance(v,np.ndarray) for v in obj]):
        value_str = "list of arrays, shapes " + ",".join([str(v.shape) for v in obj[:5]]) + " ..."
      elif self[k] is None:
        value_str = "None"
      else:
        value_str = str(self[k])
      if len(str(obj))>50: value_str += " ..."
      s.append( fmt % (k,value_str) ) 
    return "\n".join(s)

  def keys(self):
    keys = list(super().keys())
    keys = [k for k in keys if k != 'filename' ]
    return keys

  def save(self,fname=None):
    if fname is None: fname = self.filename
    assert fname is not None
    save(fname,self)