bazarr/libs/json_tricks/decoders.py

from datetime import datetime, date, time, timedelta
from fractions import Fraction
from importlib import import_module
from collections import OrderedDict
from decimal import Decimal
from logging import warning
from json_tricks import NoPandasException, NoNumpyException


class DuplicateJsonKeyException(Exception):
	""" Trying to load a json map which contains duplicate keys, but allow_duplicates is False """


class TricksPairHook(object):
	"""
	Hook that converts json maps to the appropriate python type (dict or OrderedDict)
	and then runs any number of hooks on the individual maps.
	"""
	def __init__(self, ordered=True, obj_pairs_hooks=None, allow_duplicates=True):
		"""
		:param ordered: True if maps should retain their ordering.
		:param obj_pairs_hooks: An iterable of hooks to apply to elements.
		"""
		self.map_type = OrderedDict
		if not ordered:
			self.map_type = dict
		self.obj_pairs_hooks = []
		if obj_pairs_hooks:
			self.obj_pairs_hooks = list(obj_pairs_hooks)
		self.allow_duplicates = allow_duplicates

	def __call__(self, pairs):
		if not self.allow_duplicates:
			known = set()
			for key, value in pairs:
				if key in known:
					raise DuplicateJsonKeyException(('Trying to load a json map which contains a' +
						' duplicate key "{0:}" (but allow_duplicates is False)').format(key))
				known.add(key)
		map = self.map_type(pairs)
		for hook in self.obj_pairs_hooks:
			map = hook(map)
		return map


def json_date_time_hook(dct):
	"""
	Return an encoded date, time, datetime or timedelta to it's python representation, including optional timezone.

	:param dct: (dict) json encoded date, time, datetime or timedelta
	:return: (date/time/datetime/timedelta obj) python representation of the above
	"""
	def get_tz(dct):
		if not 'tzinfo' in dct:
			return None
		try:
			import pytz
		except ImportError as err:
			raise ImportError(('Tried to load a json object which has a timezone-aware (date)time. '
				'However, `pytz` could not be imported, so the object could not be loaded. '
				'Error: {0:}').format(str(err)))
		return pytz.timezone(dct['tzinfo'])

	if isinstance(dct, dict):
		if '__date__' in dct:
			return date(year=dct.get('year', 0), month=dct.get('month', 0), day=dct.get('day', 0))
		elif '__time__' in dct:
			tzinfo = get_tz(dct)
			return time(hour=dct.get('hour', 0), minute=dct.get('minute', 0), second=dct.get('second', 0),
				microsecond=dct.get('microsecond', 0), tzinfo=tzinfo)
		elif '__datetime__' in dct:
			tzinfo = get_tz(dct)
			return datetime(year=dct.get('year', 0), month=dct.get('month', 0), day=dct.get('day', 0),
				hour=dct.get('hour', 0), minute=dct.get('minute', 0), second=dct.get('second', 0),
				microsecond=dct.get('microsecond', 0), tzinfo=tzinfo)
		elif '__timedelta__' in dct:
			return timedelta(days=dct.get('days', 0), seconds=dct.get('seconds', 0),
				microseconds=dct.get('microseconds', 0))
	return dct


def json_complex_hook(dct):
	"""
	Return an encoded complex number to it's python representation.

	:param dct: (dict) json encoded complex number (__complex__)
	:return: python complex number
	"""
	if isinstance(dct, dict):
		if '__complex__' in dct:
			parts = dct['__complex__']
			assert len(parts) == 2
			return parts[0] + parts[1] * 1j
	return dct


def numeric_types_hook(dct):
	if isinstance(dct, dict):
		if '__decimal__' in dct:
			return Decimal(dct['__decimal__'])
		if '__fraction__' in dct:
			return Fraction(numerator=dct['numerator'], denominator=dct['denominator'])
	return dct


class ClassInstanceHook(object):
	"""
	This hook tries to convert json encoded by class_instance_encoder back to it's original instance.
	It only works if the environment is the same, e.g. the class is similarly importable and hasn't changed.
	"""
	def __init__(self, cls_lookup_map=None):
		self.cls_lookup_map = cls_lookup_map or {}

	def __call__(self, dct):
		if isinstance(dct, dict) and '__instance_type__' in dct:
			mod, name = dct['__instance_type__']
			attrs = dct['attributes']
			if mod is None:
				try:
					Cls = getattr((__import__('__main__')), name)
				except (ImportError, AttributeError) as err:
					if not name in self.cls_lookup_map:
						raise ImportError(('class {0:s} seems to have been exported from the main file, which means '
							'it has no module/import path set; you need to provide cls_lookup_map which maps names '
							'to classes').format(name))
					Cls = self.cls_lookup_map[name]
			else:
				imp_err = None
				try:
					module = import_module('{0:}'.format(mod, name))
				except ImportError as err:
					imp_err = ('encountered import error "{0:}" while importing "{1:}" to decode a json file; perhaps '
						'it was encoded in a different environment where {1:}.{2:} was available').format(err, mod, name)
				else:
					if not hasattr(module, name):
						imp_err = 'imported "{0:}" but could find "{1:}" inside while decoding a json file (found {2:}'.format(
							module, name, ', '.join(attr for attr in dir(module) if not attr.startswith('_')))
					Cls = getattr(module, name)
				if imp_err:
					if 'name' in self.cls_lookup_map:
						Cls = self.cls_lookup_map[name]
					else:
						raise ImportError(imp_err)
			try:
				obj = Cls.__new__(Cls)
			except TypeError:
				raise TypeError(('problem while decoding instance of "{0:s}"; this instance has a special '
					'__new__ method and can\'t be restored').format(name))
			if hasattr(obj, '__json_decode__'):
				obj.__json_decode__(**attrs)
			else:
				obj.__dict__ = dict(attrs)
			return  obj
		return dct


def json_set_hook(dct):
	"""
	Return an encoded set to it's python representation.
	"""
	if isinstance(dct, dict):
		if '__set__' in dct:
			return set((tuple(item) if isinstance(item, list) else item) for item in dct['__set__'])
	return dct


def pandas_hook(dct):
	if '__pandas_dataframe__' in dct or '__pandas_series__' in dct:
		# todo: this is experimental
		if not getattr(pandas_hook, '_warned', False):
			pandas_hook._warned = True
			warning('Pandas loading support in json-tricks is experimental and may change in future versions.')
	if '__pandas_dataframe__' in dct:
		try:
			from pandas import DataFrame
		except ImportError:
			raise NoPandasException('Trying to decode a map which appears to represent a pandas data structure, but pandas appears not to be installed.')
		from numpy import dtype, array
		meta = dct.pop('__pandas_dataframe__')
		indx = dct.pop('index') if 'index' in dct else None
		dtypes = dict((colname, dtype(tp)) for colname, tp in zip(meta['column_order'], meta['types']))
		data = OrderedDict()
		for name, col in dct.items():
			data[name] = array(col, dtype=dtypes[name])
		return DataFrame(
			data=data,
			index=indx,
			columns=meta['column_order'],
			# mixed `dtypes` argument not supported, so use duct of numpy arrays
		)
	elif '__pandas_series__' in dct:
		from pandas import Series
		from numpy import dtype, array
		meta = dct.pop('__pandas_series__')
		indx = dct.pop('index') if 'index' in dct else None
		return Series(
			data=dct['data'],
			index=indx,
			name=meta['name'],
			dtype=dtype(meta['type']),
		)
	return dct


def nopandas_hook(dct):
	if isinstance(dct, dict) and ('__pandas_dataframe__' in dct or '__pandas_series__' in dct):
		raise NoPandasException(('Trying to decode a map which appears to represent a pandas '
			'data structure, but pandas support is not enabled, perhaps it is not installed.'))
	return dct


def json_numpy_obj_hook(dct):
	"""
	Replace any numpy arrays previously encoded by NumpyEncoder to their proper
	shape, data type and data.

	:param dct: (dict) json encoded ndarray
	:return: (ndarray) if input was an encoded ndarray
	"""
	if isinstance(dct, dict) and '__ndarray__' in dct:
		try:
			from numpy import asarray
			import numpy as nptypes
		except ImportError:
			raise NoNumpyException('Trying to decode a map which appears to represent a numpy '
				'array, but numpy appears not to be installed.')
		order = 'A'
		if 'Corder' in dct:
			order = 'C' if dct['Corder'] else 'F'
		if dct['shape']:
			return asarray(dct['__ndarray__'], dtype=dct['dtype'], order=order)
		else:
			dtype = getattr(nptypes, dct['dtype'])
			return dtype(dct['__ndarray__'])
	return dct


def json_nonumpy_obj_hook(dct):
	"""
	This hook has no effect except to check if you're trying to decode numpy arrays without support, and give you a useful message.
	"""
	if isinstance(dct, dict) and '__ndarray__' in dct:
		raise NoNumpyException(('Trying to decode a map which appears to represent a numpy array, '
			'but numpy support is not enabled, perhaps it is not installed.'))
	return dct