text: # -*- coding: utf-8 -*-
  '''Chemical Engineering Design Library (ChEDL). Utilities for process modeling.
  Copyright (C) 2021 Caleb Bell <Caleb.Andrew.Bell@gmail.com>
  
  Permission is hereby granted, free of charge, to any person obtaining a copy
  of this software and associated documentation files (the "Software"), to deal
  in the Software without restriction, including without limitation the rights
  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  copies of the Software, and to permit persons to whom the Software is
  furnished to do so, subject to the following conditions:
  
  The above copyright notice and this permission notice shall be included in all
  copies or substantial portions of the Software.
  
  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  SOFTWARE.
  
  This module contains functionality for serializing classes.
  
  For reporting bugs, adding feature requests, or submitting pull requests,
  please use the `GitHub issue tracker <https://github.com/CalebBell/chemicals/>`_.
  
  .. contents:: :local:
  '''
  # This module SHOULD NOT import anything from thermo
  from fluids.numerics import numpy as np
  from chemicals.utils import PY37
  
  __all__ = ['object_from_json', 'json_default']
  try:
      array = np.array
      int_types = frozenset([np.short, np.ushort, np.intc, np.uintc, np.int_,
                             np.uint, np.longlong, np.ulonglong])
      float_types = frozenset([np.float16, np.single, np.double, np.longdouble,
                               np.csingle, np.cdouble, np.clongdouble])
      ndarray = np.ndarray
  
  except:
      pass
  
  
  BasicNumpyEncoder = None
  def build_numpy_encoder():
      '''Create a basic numpy encoder for json applications. All np ints become
      Python ints; numpy floats become python floats; and all arrays become
      lists-of-lists of floats, ints, bools, or complexes according to Python's
      rules.
      '''
      global BasicNumpyEncoder, json, int_types, float_types
  
      import json
      JSONEncoder = json.JSONEncoder
  
      class BasicNumpyEncoder(JSONEncoder):
          def default(self, obj):
              t = type(obj)
              if t is ndarray:
                  return obj.tolist()
              elif t in int_types:
                  return int(obj)
              elif t in float_types:
                  return float(obj)
              return JSONEncoder.default(self, obj)
  
  def arrays_to_lists(obj):
      t = type(obj)
      if t is dict:
          # Do not modify objects in place
          obj = obj.copy()
          for k, v in obj.items():
              obj[k] = arrays_to_lists(v)
      elif t is tuple:
          return tuple(arrays_to_lists(v) for v in obj)
      elif t is set:
          # Can't put arrays in sets
          return obj
  #        return set(arrays_to_lists(v) for v in obj)
      elif t is ndarray:
          return obj.tolist()
      elif t in int_types:
          return int(obj)
      elif t in float_types:
          return float(obj)
      return obj
  
  
  def naive_lists_to_arrays(obj):
      t = type(obj)
      if t is dict:
          # Do not modify objects in place
          obj = obj.copy()
          for k, v in obj.items():
              obj[k] = naive_lists_to_arrays(v)
      elif t is tuple:
          return tuple(naive_lists_to_arrays(v) for v in obj)
      elif t is set:
          return set(naive_lists_to_arrays(v) for v in obj)
      elif t is list:
          if len(obj) >= 2 and type(obj[0]) is list:
              # Handle tuples of different sized arrays
              try:
                  length = len(obj[0])
                  for v in obj[1:]:
                      if len(v) != length:
                          return tuple(array(v) for v in obj)
              except:
                  pass
          return array(obj)
      return obj
  
  BasicNumpyDecoder = None
  def build_numpy_decoder():
      global BasicNumpyDecoder, json
      import json
  
      class BasicNumpyDecoder(json.JSONDecoder):
          def __init__(self, *args, **kwargs):
              json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs)
  
          def object_hook(self, obj):
              return naive_lists_to_arrays(obj)
  
  
  def _load_orjson():
      global orjson
      import orjson
  
  def dump_json_np(obj, library='json'):
      '''Serialization tool that handles numpy arrays. By default this will
      use the standard library json, but this can also use orjson.'''
      if library == 'json':
          if BasicNumpyEncoder is None:
              build_numpy_encoder()
          return json.dumps(obj, cls=BasicNumpyEncoder)
      elif library == 'orjson':
          if orjson is None:
              _load_orjson()
          opt = orjson.OPT_SERIALIZE_NUMPY
          return orjson.dumps(obj, option=opt)
  
  def load_json_np(obj, library='json'):
      '''Serialization tool that handles numpy arrays. By default this will
      use the standard library json, but this can also use orjson.'''
      if library == 'json':
          if BasicNumpyDecoder is None:
              build_numpy_decoder()
          return json.loads(obj, cls=BasicNumpyDecoder)
      elif library == 'orjson':
          if orjson is None:
              _load_orjson()
          opt = orjson.OPT_SERIALIZE_NUMPY
          return orjson.loads(obj, option=opt)
  
  json_loaded = False
  def _load_json():
      global json
      import json
      json_loaded = True
  
  global json, orjson
  orjson = None
  
  if PY37:
      def __getattr__(name):
          global json, json_loaded
          if name == 'json':
              import json
              json_loaded = True
              return json
          raise AttributeError("module %s has no attribute %s" %(__name__, name))
  else:
      import json
      json_loaded = True
  
  
  
  
  
  def object_from_json(json_object):
      if 'py/object' in json_object:
          pth = json_object['py/object']
          # TODO: Cache these lookups
          bits = pth.split('.')
          mod = '.'.join(bits[:-1])
          cls_name = bits[-1]
          obj = getattr(sys.modules[mod], cls_name)
  
          return obj.from_json(json_object)
      raise ValueError("Could not recognize object")
  
  
  def json_default(obj):
      if hasattr(obj, 'as_json'):
          return obj.as_json()
      raise TypeError()
  