def middleware(method, params):
response = make_request(method, params)
if 'result' in response:
result = response['result']
if is_dict(result) and not isinstance(result, AttributeDict):
return assoc(response, 'result', AttributeDict.recursive(result))
else:
return response
else:
return response
def test_attributedict_dict_in_list_in_dict():
data = {'instructions': [
0,
1,
'neither shalt thou count, excepting that thou then proceedeth to three',
{'if_naughty': 'snuff it'},
'shalt thou not count',
'right out',
]}
attrdict = AttributeDict.recursive(data)
assert attrdict.instructions[3].if_naughty == 'snuff it'
def _castAttributeDict(self, maybe_dict):
"""Return an AttributeDict as is provided by web3 middleware."""
if is_dict(maybe_dict) and not isinstance(maybe_dict, AttributeDict):
return AttributeDict.recursive(maybe_dict)
else:
return maybe_dict
def get_event_data(event_abi, log_entry):
"""
Given an event ABI and a log entry for that event, return the decoded
event data
"""
if event_abi['anonymous']:
log_topics = log_entry['topics']
elif not log_entry['topics']:
raise MismatchedABI(
"Expected non-anonymous event to have 1 or more topics")
elif event_abi_to_log_topic(event_abi) != log_entry['topics'][0]:
raise MismatchedABI(
"The event signature did not match the provided ABI")
else:
log_topics = log_entry['topics'][1:]
log_topics_abi = get_indexed_event_inputs(event_abi)
log_topic_normalized_inputs = normalize_event_input_types(log_topics_abi)
log_topic_types = get_event_abi_types_for_decoding(
log_topic_normalized_inputs)
log_topic_names = get_abi_input_names({'inputs': log_topics_abi})
if len(log_topics) != len(log_topic_types):
raise ValueError("Expected {0} log topics. Got {1}".format(
len(log_topic_types),
len(log_topics),
))
log_data = hexstr_if_str(to_bytes, log_entry['data'])
log_data_abi = exclude_indexed_event_inputs(event_abi)
log_data_normalized_inputs = normalize_event_input_types(log_data_abi)
log_data_types = get_event_abi_types_for_decoding(
log_data_normalized_inputs)
log_data_names = get_abi_input_names({'inputs': log_data_abi})
# sanity check that there are not name intersections between the topic
# names and the data argument names.
duplicate_names = set(log_topic_names).intersection(log_data_names)
if duplicate_names:
raise ValueError(
"Invalid Event ABI: The following argument names are duplicated "
"between event inputs: '{0}'".format(', '.join(duplicate_names)))
decoded_log_data = decode_abi(log_data_types, log_data)
normalized_log_data = map_abi_data(BASE_RETURN_NORMALIZERS, log_data_types,
decoded_log_data)
decoded_topic_data = [
decode_single(topic_type, topic_data)
for topic_type, topic_data in zip(log_topic_types, log_topics)
]
normalized_topic_data = map_abi_data(BASE_RETURN_NORMALIZERS,
log_topic_types, decoded_topic_data)
event_args = dict(
itertools.chain(
zip(log_topic_names, normalized_topic_data),
zip(log_data_names, normalized_log_data),
))
event_data = {
'args': event_args,
'event': event_abi['name'],
'logIndex': log_entry['logIndex'],
'transactionIndex': log_entry['transactionIndex'],
'transactionHash': log_entry['transactionHash'],
'address': log_entry['address'],
'blockHash': log_entry['blockHash'],
'blockNumber': log_entry['blockNumber'],
}
return AttributeDict.recursive(event_data)
def get_event_data(event_abi, log_entry):
"""
Given an event ABI and a log entry for that event, return the decoded
event data
"""
if event_abi['anonymous']:
log_topics = log_entry['topics']
elif not log_entry['topics']:
raise MismatchedABI("Expected non-anonymous event to have 1 or more topics")
elif event_abi_to_log_topic(event_abi) != log_entry['topics'][0]:
raise MismatchedABI("The event signature did not match the provided ABI")
else:
log_topics = log_entry['topics'][1:]
log_topics_abi = get_indexed_event_inputs(event_abi)
log_topic_normalized_inputs = normalize_event_input_types(log_topics_abi)
log_topic_types = get_event_abi_types_for_decoding(log_topic_normalized_inputs)
log_topic_names = get_abi_input_names({'inputs': log_topics_abi})
if len(log_topics) != len(log_topic_types):
raise ValueError("Expected {0} log topics. Got {1}".format(
len(log_topic_types),
len(log_topics),
))
log_data = hexstr_if_str(to_bytes, log_entry['data'])
log_data_abi = exclude_indexed_event_inputs(event_abi)
log_data_normalized_inputs = normalize_event_input_types(log_data_abi)
log_data_types = get_event_abi_types_for_decoding(log_data_normalized_inputs)
log_data_names = get_abi_input_names({'inputs': log_data_abi})
# sanity check that there are not name intersections between the topic
# names and the data argument names.
duplicate_names = set(log_topic_names).intersection(log_data_names)
if duplicate_names:
raise ValueError(
"Invalid Event ABI: The following argument names are duplicated "
"between event inputs: '{0}'".format(', '.join(duplicate_names))
)
decoded_log_data = decode_abi(log_data_types, log_data)
normalized_log_data = map_abi_data(
BASE_RETURN_NORMALIZERS,
log_data_types,
decoded_log_data
)
decoded_topic_data = [
decode_single(topic_type, topic_data)
for topic_type, topic_data
in zip(log_topic_types, log_topics)
]
normalized_topic_data = map_abi_data(
BASE_RETURN_NORMALIZERS,
log_topic_types,
decoded_topic_data
)
event_args = dict(itertools.chain(
zip(log_topic_names, normalized_topic_data),
zip(log_data_names, normalized_log_data),
))
event_data = {
'args': event_args,
'event': event_abi['name'],
'logIndex': log_entry['logIndex'],
'transactionIndex': log_entry['transactionIndex'],
'transactionHash': log_entry['transactionHash'],
'address': log_entry['address'],
'blockHash': log_entry['blockHash'],
'blockNumber': log_entry['blockNumber'],
}
return AttributeDict.recursive(event_data)
def test_attributedict_sequence_with_dict(sequence):
data = sequence(['a', {'found': True}, 'c'])
dict_in_sequence = AttributeDict.recursive(data)
assert dict_in_sequence[1].found is True
def test_attributedict_recursive_dict():
w = AttributeDict.recursive({'x': {'y': {'z': 8}}})
assert w.x.y.z == 8
def test_attributedict_set_in_recursive_dict():
data = {'mydict': {'myset': {'found'}}}
attrdict = AttributeDict.recursive(data)
assert 'found' in attrdict.mydict.myset
