Using ScaleType objects

The result of the previous storage query example is a ScaleType object, more specific a Struct.

The nested object structure of this account_info object is as follows:

account_info = <AccountInfo(value={'nonce': <U32(value=5)>, 'consumers': <U32(value=0)>, 'providers': <U32(value=1)>, 'sufficients': <U32(value=0)>, 'data': <AccountData(value={'free': 1152921503981846391, 'reserved': 0, 'misc_frozen': 0, 'fee_frozen': 0})>})>

Every ScaleType have the following characteristics:

Shorthand lookup of nested types

Inside the AccountInfo struct there are several U32 objects that represents for example a nonce or the amount of provider, also another struct object AccountData which contains more nested types.

To access these nested structures you can access those formally using:

account_info.value_object['data'].value_object['free']

As a convenient shorthand you can also use:

account_info['data']['free']

ScaleType objects can also be automatically converted to an iterable, so if the object is for example the others in the result Struct of Staking.eraStakers can be iterated via:

for other_info in era_stakers['others']:
    print(other_info['who'], other_info['value'])

Serializable

Each ScaleType holds a complete serialized version of itself in the account_info.serialize() property, so it can easily store or used to create JSON strings.

So the whole result of account_info.serialize() will be a dict containing the following:

{
    "nonce": 5,
    "consumers": 0,
    "providers": 1,
    "sufficients": 0,
    "data": {
        "free": 1152921503981846391,
        "reserved": 0,
        "misc_frozen": 0,
        "fee_frozen": 0
    }
}

Comparing values with ScaleType objects

It is possible to compare ScaleType objects directly to Python primitives, internally the serialized value attribute is compared:

metadata_obj[1][1]['extrinsic']['version'] # '<U8(value=4)>'
metadata_obj[1][1]['extrinsic']['version'] == 4 # True