def get_field_markup_with_helper(self, id):
x = getattr(fixtures, id)
if request.method == 'POST':
response.headers['Content-Type'] = 'application/json'
out = {tuple(k.split('.')): v for k, v in request.params.items()}
out = unflatten(out)
return to_json(out)
else:
params = dict(request.params)
k = params.pop('field', 'title')
field = x.get_field(k)
action = params.pop('action', 'edit')
prefix = params.pop('prefix', id)
extra_vars = copy.deepcopy(params)
extra_vars.update({
'helper': True,
'field': field,
'action': str(action),
'name_prefix': str(prefix),
})
return render('tests/field.html', extra_vars=extra_vars)
def get_field_markup_with_helper(self, id):
x = getattr(fixtures, id)
if request.method == 'POST':
response.headers['Content-Type'] = 'application/json'
out = { tuple(k.split('.')): v for k, v in request.params.items() }
out = unflatten(out)
return to_json(out)
else:
params = dict(request.params)
k = params.pop('field', 'title')
field = x.get_field(k)
action = params.pop('action', 'edit')
prefix = params.pop('prefix', id)
extra_vars = copy.deepcopy(params)
extra_vars.update({
'helper': True,
'field': field,
'action': str(action),
'name_prefix': str(prefix),
})
return render('tests/field.html', extra_vars=extra_vars)
def get_field_markup(self, id):
x = getattr(fixtures, id)
if request.method == 'POST':
response.headers['Content-Type'] = 'application/json'
out = { tuple(k.split('.')): v for k, v in request.params.items() }
out = unflatten(out)
return to_json(out)
else:
params = dict(request.params)
k = params.pop('field', 'title')
action = params.pop('action', 'edit')
prefix = params.pop('prefix', id)
field = x.get_field(k)
field_markup = markup_for_field(str(action),
field, name_prefix=str(prefix), errors=None, data=params)
return render('tests/field.html', extra_vars={
'field_markup': field_markup })
def get_field_markup(self, id):
x = getattr(fixtures, id)
if request.method == 'POST':
response.headers['Content-Type'] = 'application/json'
out = {tuple(k.split('.')): v for k, v in request.params.items()}
out = unflatten(out)
return to_json(out)
else:
params = dict(request.params)
k = params.pop('field', 'title')
action = params.pop('action', 'edit')
prefix = params.pop('prefix', id)
field = x.get_field(k)
field_markup = markup_for_field(str(action),
field,
name_prefix=str(prefix),
errors=None,
data=params)
return render('tests/field.html',
extra_vars={'field_markup': field_markup})
def from_dict(self, d, is_flat=None, opts={}):
'''Convert (i.e. load) from a (flat or nested) dict.
The supported options (opts) are:
* update: bool, str (default: False)
Indicate whether input data should update self's relevant attributes.
If this option is:
- not set: self will be fully reloaded from scratch
- set to True or 'shallow': self will be updated in shallow mode
- set to 'deep': self will be updated in deep (recursive) mode
* use-defaults: bool (default: True)
Indicate whether a missing/None value should be initialized to a field-wise
default value (or instead, be set to None). This option has no effect if an
update is carried out (i.e it only affects a reload).
* unserialize-keys: bool (default: False)
Indicate whether keys need to be unserialized before anything else
happens. This option has no effect if we are loading from a nested dict.
* key-prefix: str (default: None)
The string prefix for keys if they are to be unserialized.
* unserialize-values: str (default: False)
Indicate whether values are to unserialized. If given as a string, will be
interpreted as a serialization format (see serializers.supported_formats)
'''
assert isinstance(d, dict)
cls = type(self)
# Preprocess and sanitize options
opts = copy.copy(opts) # to modify it
unserialize_values = opts.get('unserialize-values', False)
if unserialize_values:
if isinstance(unserialize_values, (bool, int)):
unserialize_values = 'default'
else:
unserialize_values = str(unserialize_values)
opts['unserialize-values'] = unserialize_values
update = opts.get('update', False)
if update:
if isinstance(update, (bool, int)):
update = 'shallow'
else:
update = str(update)
if not update in ['shallow', 'deep']:
update = 'shallow'
opts['update'] = update
# Decide if input is a flattened dict
if is_flat is None:
is_flat = isinstance(d.iterkeys().next(), tuple)
if is_flat:
unserialize_keys = opts.get('unserialize-keys', False)
if unserialize_keys:
key_prefix = opts.get('key-prefix')
kser = serializer_for_key_tuple(key_prefix)
is_key = kser.get_key_predicate(basestring, strict=True)
d = {kser.loads(k): v for k, v in d.iteritems() if is_key(k)}
d = dictization.unflatten(d)
# Load self
self.load(d, opts)
# Allow method chaining
return self
def from_dict(self, d, is_flat=None, opts={}):
'''Convert (i.e. load) from a (flat or nested) dict.
The supported options (opts) are:
* update: bool, str (default: False)
Indicate whether input data should update self's relevant attributes.
If this option is:
- not set: self will be fully reloaded from scratch
- set to True or 'shallow': self will be updated in shallow mode
- set to 'deep': self will be updated in deep (recursive) mode
* use-defaults: bool (default: True)
Indicate whether a missing/None value should be initialized to a field-wise
default value (or instead, be set to None). This option has no effect if an
update is carried out (i.e it only affects a reload).
* unserialize-keys: bool (default: False)
Indicate whether keys need to be unserialized before anything else
happens. This option has no effect if we are loading from a nested dict.
* key-prefix: str (default: None)
The string prefix for keys if they are to be unserialized.
* unserialize-values: str (default: False)
Indicate whether values are to unserialized. If given as a string, will be
interpreted as a serialization format (see serializers.supported_formats)
'''
assert isinstance(d, dict)
cls = type(self)
# Preprocess and sanitize options
opts = copy.copy(opts) # to modify it
unserialize_values = opts.get('unserialize-values', False)
if unserialize_values:
if isinstance(unserialize_values, (bool, int)):
unserialize_values = 'default'
else:
unserialize_values = str(unserialize_values)
opts['unserialize-values'] = unserialize_values
update = opts.get('update', False)
if update:
if isinstance(update, (bool, int)):
update = 'shallow'
else:
update = str(update)
if not update in ['shallow', 'deep']:
update = 'shallow'
opts['update'] = update
# Decide if input is a flattened dict
if is_flat is None:
is_flat = isinstance(d.iterkeys().next(), tuple)
if is_flat:
unserialize_keys = opts.get('unserialize-keys', False)
if unserialize_keys:
key_prefix = opts.get('key-prefix')
kser = serializer_for_key_tuple(key_prefix)
is_key = kser.get_key_predicate(basestring, strict=True)
d = { kser.loads(k): v for k, v in d.iteritems() if is_key(k) }
d = dictization.unflatten(d)
# Load self
self.load(d, opts)
# Allow method chaining
return self
"a": [1.4, 7.6, 9.7, 5.9, 5.0, 9.1, 11.3],
"b": [4.9],
"c": {
# Here, unflatten() should detect a list
u"0": 99,
u"1": 100,
u"2": 199,
},
},
},
u"author": u"lalakis",
}
d1 = dictization.flatten(d)
d2 = dictization.unflatten(d1)
def test_flattened_1():
for k in sorted(d1):
v = d1.get(k)
assert isinstance(v, basestring) or isinstance(v, float) or isinstance(v, int), "%r is not scalar" % (v)
@raises(AssertionError)
def test_inversed_1():
s0 = json.dumps(d)
s2 = json.dumps(d2)
# Should fail because d[u'measurements'][u'samples']['c'] is converted to a list
eq_(s0, s2)
'a': [ 1.4 ,7.6, 9.7, 5.9, 5.0, 9.1, 11.3, ],
'b': [ 4.9 ],
'c': {
# Here, unflatten() should detect a list
u'0': 99,
u'1': 100,
u'2': 199,
},
},
},
u'author': u'lalakis',
}
d1 = dictization.flatten(d)
d2 = dictization.unflatten(d1)
def test_flattened_1():
for k in sorted(d1):
v = d1.get(k)
assert isinstance(v, basestring) or isinstance(v, float) or isinstance(v, int), \
'%r is not scalar' %(v)
@raises(AssertionError)
def test_inversed_1():
s0 = json.dumps(d)
s2 = json.dumps(d2)
# Should fail because d[u'measurements'][u'samples']['c'] is converted to a list
eq_(s0, s2)
def test_inversed_2():
