def _get_flattener(self, obj):
if PY2 and isinstance(obj, file):
return self._flatten_file
if util.is_primitive(obj):
return lambda obj: obj
if util.is_bytes(obj):
return self._flatten_bytestring
list_recurse = self._list_recurse
if util.is_list(obj):
if self._mkref(obj):
return list_recurse
else:
self._push()
return self._getref
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}
if util.is_set(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}
if util.is_dictionary(obj):
return self._flatten_dict_obj
if util.is_type(obj):
return _mktyperef
if util.is_object(obj):
return self._ref_obj_instance
if util.is_module_function(obj):
return self._flatten_function
# instance methods, lambdas, old style classes...
self._pickle_warning(obj)
return None
def _get_flattener(self, obj):
if PY2 and isinstance(obj, file):
return self._flatten_file
if util.is_primitive(obj):
return lambda obj: obj
if util.is_bytes(obj):
return self._flatten_bytestring
list_recurse = self._list_recurse
if util.is_list(obj):
if self._mkref(obj):
return list_recurse
else:
self._push()
return self._getref
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}
if util.is_set(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}
if util.is_dictionary(obj):
return self._flatten_dict_obj
if util.is_type(obj):
return _mktyperef
if util.is_object(obj):
return self._ref_obj_instance
if util.is_module_function(obj):
return self._flatten_function
# instance methods, lambdas, old style classes...
self._pickle_warning(obj)
return None
def _get_flattener(self, obj):
if util.is_primitive(obj):
return lambda obj: obj
list_recurse = self._list_recurse
if util.is_list(obj):
if self._mkref(obj):
return list_recurse
else:
self._push()
return self._getref
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}
if util.is_set(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}
if util.is_dictionary(obj):
return self._flatten_dict_obj
if util.is_type(obj):
return _mktyperef
if util.is_object(obj):
return self._ref_obj_instance
# else, what else? (methods, functions, old style classes...)
return None
def _get_flattener(self, obj):
if util.is_primitive(obj):
return lambda obj: obj
list_recurse = self._list_recurse
if util.is_list(obj):
if self._mkref(obj):
return list_recurse
else:
self._push()
return self._getref
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}
if util.is_set(obj):
if not self.unpicklable:
return list_recurse
return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}
if util.is_dictionary(obj):
return self._flatten_dict_obj
if util.is_type(obj):
return _mktyperef
if util.is_object(obj):
return self._ref_obj_instance
# else, what else? (methods, functions, old style classes...)
return None
def flatten(self, obj):
"""Takes an object and returns a JSON-safe representation of it.
Simply returns any of the basic builtin datatypes
>>> p = Pickler()
>>> p.flatten('hello world')
'hello world'
>>> p.flatten(u'hello world')
u'hello world'
>>> p.flatten(49)
49
>>> p.flatten(350.0)
350.0
>>> p.flatten(True)
True
>>> p.flatten(False)
False
>>> r = p.flatten(None)
>>> r is None
True
>>> p.flatten(False)
False
>>> p.flatten([1, 2, 3, 4])
[1, 2, 3, 4]
>>> p.flatten((1,2,))[tags.TUPLE]
[1, 2]
>>> p.flatten({'key': 'value'})
{'key': 'value'}
"""
self._push()
if self._depth == self._max_depth:
return self._pop(repr(obj))
if util.is_primitive(obj):
return self._pop(obj)
if util.is_list(obj):
if self._mkref(obj):
return self._pop([self.flatten(v) for v in obj])
else:
return self._getref(obj)
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
if self.unpicklable:
return self._pop({tags.TUPLE: [self.flatten(v) for v in obj]})
else:
return self._pop([self.flatten(v) for v in obj])
if util.is_set(obj):
if self.unpicklable:
return self._pop({tags.SET: [self.flatten(v) for v in obj]})
else:
return self._pop([self.flatten(v) for v in obj])
if util.is_dictionary(obj):
return self._pop(self._flatten_dict_obj(obj, obj.__class__()))
if util.is_type(obj):
return self._pop(_mktyperef(obj))
if util.is_object(obj):
if self._mkref(obj):
# We've never seen this object so return its
# json representation.
return self._pop(self._flatten_obj_instance(obj))
else:
# We've seen this object before so place an object
# reference tag in the data. This avoids infinite recursion
# when processing cyclical objects.
return self._pop(self._getref(obj))
# else, what else? (methods, functions, old style classes...)
return None
def test_is_list_other(self):
self.assertFalse(is_list(1))
self.assertFalse(is_set(1))
self.assertFalse(is_tuple(1))
def test_is_list_dict(self):
self.assertFalse(is_list({'key':'value'}))
self.assertFalse(is_set({'key':'value'}))
self.assertFalse(is_tuple({'key':'value'}))
def test_is_list_set(self):
self.assertTrue(is_set(set([1, 2])))
def test_is_list_set(self):
self.assertTrue(util.is_set({1, 2}))
def test_is_list_set(self):
self.assertTrue(util.is_set({1, 2}))
def flatten(self, obj):
"""Takes an object and returns a JSON-safe representation of it.
Simply returns any of the basic builtin datatypes
>>> p = Pickler()
>>> p.flatten('hello world')
'hello world'
>>> p.flatten(u'hello world')
u'hello world'
>>> p.flatten(49)
49
>>> p.flatten(350.0)
350.0
>>> p.flatten(True)
True
>>> p.flatten(False)
False
>>> r = p.flatten(None)
>>> r is None
True
>>> p.flatten(False)
False
>>> p.flatten([1, 2, 3, 4])
[1, 2, 3, 4]
>>> p.flatten((1,2,))[tags.TUPLE]
[1, 2]
>>> p.flatten({'key': 'value'})
{'key': 'value'}
"""
self._push()
if self._depth == self._max_depth:
return self._pop(repr(obj))
if util.is_primitive(obj):
return self._pop(obj)
if util.is_list(obj):
return self._pop([ self.flatten(v) for v in obj ])
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
return self._pop({tags.TUPLE: [ self.flatten(v) for v in obj ]})
if util.is_set(obj):
return self._pop({tags.SET: [ self.flatten(v) for v in obj ]})
if util.is_dictionary(obj):
return self._pop(self._flatten_dict_obj(obj, obj.__class__()))
if util.is_type(obj):
return self._pop(_mktyperef(obj))
if util.is_object(obj):
data = {}
has_class = hasattr(obj, '__class__')
has_dict = hasattr(obj, '__dict__')
if self._mkref(obj):
if has_class and not util.is_repr(obj):
module, name = _getclassdetail(obj)
if self.unpicklable is True:
data[tags.OBJECT] = '%s.%s' % (module, name)
if util.is_repr(obj):
if self.unpicklable is True:
data[tags.REPR] = '%s/%s' % (obj.__class__.__module__,
repr(obj))
else:
data = unicode(obj)
return self._pop(data)
if util.is_dictionary_subclass(obj):
return self._pop(self._flatten_dict_obj(obj, data))
if util.is_noncomplex(obj):
return self._pop([self.flatten(v) for v in obj])
if has_dict:
return self._pop(self._flatten_dict_obj(obj.__dict__, data))
else:
# We've seen this object before so place an object
# reference tag in the data. This avoids infinite recursion
# when processing cyclical objects.
return self._pop(self._getref(obj))
return self._pop(data)
def test_is_list_other(self):
self.assertFalse(util.is_list(1))
self.assertFalse(util.is_set(1))
self.assertFalse(util.is_tuple(1))
def test_is_list_dict(self):
self.assertFalse(util.is_list({'key': 'value'}))
self.assertFalse(util.is_set({'key': 'value'}))
self.assertFalse(util.is_tuple({'key': 'value'}))
def test_is_list_set(self):
self.assertTrue(util.is_set(set([1, 2])))
def flatten(self, obj):
"""Takes an object and returns a JSON-safe representation of it.
Simply returns any of the basic builtin datatypes
>>> p = Pickler()
>>> p.flatten('hello world')
'hello world'
>>> p.flatten(u'hello world')
u'hello world'
>>> p.flatten(49)
49
>>> p.flatten(350.0)
350.0
>>> p.flatten(True)
True
>>> p.flatten(False)
False
>>> r = p.flatten(None)
>>> r is None
True
>>> p.flatten(False)
False
>>> p.flatten([1, 2, 3, 4])
[1, 2, 3, 4]
>>> p.flatten((1,2,))[tags.TUPLE]
[1, 2]
>>> p.flatten({'key': 'value'})
{'key': 'value'}
"""
self._push()
if self._depth == self._max_depth:
return self._pop(repr(obj))
if util.is_primitive(obj):
return self._pop(obj)
if util.is_list(obj):
return self._pop([self.flatten(v) for v in obj])
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
return self._pop({tags.TUPLE: [self.flatten(v) for v in obj]})
if util.is_set(obj):
return self._pop({tags.SET: [self.flatten(v) for v in obj]})
if util.is_dictionary(obj):
return self._pop(self._flatten_dict_obj(obj, obj.__class__()))
if util.is_type(obj):
return self._pop(_mktyperef(obj))
if util.is_object(obj):
data = {}
has_class = hasattr(obj, '__class__')
has_dict = hasattr(obj, '__dict__')
if self._mkref(obj):
if has_class and not util.is_repr(obj):
module, name = _getclassdetail(obj)
if self.unpicklable is True:
data[tags.OBJECT] = '%s.%s' % (module, name)
if util.is_repr(obj):
if self.unpicklable is True:
data[tags.REPR] = '%s/%s' % (obj.__class__.__module__,
repr(obj))
else:
data = unicode(obj)
return self._pop(data)
if util.is_dictionary_subclass(obj):
return self._pop(self._flatten_dict_obj(obj, data))
if util.is_noncomplex(obj):
return self._pop([self.flatten(v) for v in obj])
if has_dict:
return self._pop(self._flatten_dict_obj(
obj.__dict__, data))
else:
# We've seen this object before so place an object
# reference tag in the data. This avoids infinite recursion
# when processing cyclical objects.
return self._pop(self._getref(obj))
return self._pop(data)
def flatten(self, obj):
"""Takes an object and returns a JSON-safe representation of it.
Simply returns any of the basic builtin datatypes
>>> p = Pickler()
>>> p.flatten('hello world')
'hello world'
>>> p.flatten(u'hello world')
u'hello world'
>>> p.flatten(49)
49
>>> p.flatten(350.0)
350.0
>>> p.flatten(True)
True
>>> p.flatten(False)
False
>>> r = p.flatten(None)
>>> r is None
True
>>> p.flatten(False)
False
>>> p.flatten([1, 2, 3, 4])
[1, 2, 3, 4]
>>> p.flatten((1,2,))[tags.TUPLE]
[1, 2]
>>> p.flatten({'key': 'value'})
{'key': 'value'}
"""
self._push()
if self._depth == self._max_depth:
return self._pop(repr(obj))
if util.is_primitive(obj):
return self._pop(obj)
if util.is_list(obj):
return self._pop([ self.flatten(v) for v in obj ])
# We handle tuples and sets by encoding them in a "(tuple|set)dict"
if util.is_tuple(obj):
return self._pop({tags.TUPLE: [ self.flatten(v) for v in obj ]})
if util.is_set(obj):
return self._pop({tags.SET: [ self.flatten(v) for v in obj ]})
if util.is_dictionary(obj):
return self._pop(self._flatten_dict_obj(obj, obj.__class__()))
if util.is_type(obj):
return self._pop(_mktyperef(obj))
if util.is_object(obj):
if self._mkref(obj):
# We've never seen this object so return its
# json representation.
return self._pop(self._flatten_obj_instance(obj))
else:
# We've seen this object before so place an object
# reference tag in the data. This avoids infinite recursion
# when processing cyclical objects.
return self._pop(self._getref(obj))
return self._pop(data)
def test_is_list_dict(self):
self.assertFalse(is_list({"key": "value"}))
self.assertFalse(is_set({"key": "value"}))
self.assertFalse(is_tuple({"key": "value"}))