scalecodec 1.0.34

Python SCALE Codec Library

Python SCALE Codec

Python SCALE Codec Library

Description

Most of the data that the Substrate RPCs output is encoded with the SCALE Codec. This codec is used by the Substrate nodes' internal runtime. In order to get to meaningful data this data will need to be decoded. The Python SCALE Codec Library will specialize in this task.

Documentation

https://polkascan.github.io/py-scale-codec/

Installation

pip install scalecodec

Examples (MetadataV14 runtimes and higher)

Encode a Call

runtime_config = RuntimeConfigurationObject()
# This types are all hardcoded types needed to decode metadata types
runtime_config.update_type_registry(load_type_registry_preset(name="metadata_types"))

# Decode retrieved metadata from the RPC
metadata = runtime_config.create_scale_object(
    'MetadataVersioned', data=ScaleBytes(response.get('result'))
)
metadata.decode()

# Add the embedded type registry to the runtime config
runtime_config.add_portable_registry(metadata)

call = runtime_config.create_scale_object(
    "Call", metadata=metadata
)
call.encode({
    "call_module": "Balances",
    "call_function": "transfer",
    "call_args": {"dest": "5GNJqTPyNqANBkUVMN1LPPrxXnFouWXoe2wNSmmEoLctxiZY", "value": 3},
})

Decode the result of a state_getStorageAt RPC call

event_data = "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"

system_pallet = metadata.get_metadata_pallet("System")
event_storage_function = system_pallet.get_storage_function("Events")

event = runtime_config.create_scale_object(
    event_storage_function.get_value_type_string(), metadata=metadata
)
print(event.decode(ScaleBytes(event_data)))

Retrieve type decomposition information of a RegistryType:

pallet = metadata.get_metadata_pallet("System")
storage_function = pallet.get_storage_function("BlockHash")

param_type_string = storage_function.get_params_type_string()
param_type_obj = runtime_config.create_scale_object(param_type_string[0])

type_info = param_type_obj.scale_info_type.retrieve_type_decomposition()

print(type_info) 
# {'primitive': 'u32'}

Examples (prior to MetadataV14)

Decode a SCALE-encoded Compact<Balance>

RuntimeConfiguration().update_type_registry(load_type_registry_preset("default"))
RuntimeConfiguration().update_type_registry(load_type_registry_preset("kusama"))
obj = RuntimeConfiguration().create_scale_object('Compact<Balance>', data=ScaleBytes("0x130080cd103d71bc22"))
obj.decode()
print(obj.value)

Encode to Compact<Balance>

RuntimeConfiguration().update_type_registry(load_type_registry_preset("default"))
obj = RuntimeConfiguration().create_scale_object('Compact<Balance>')
scale_data = obj.encode(2503000000000000000)
print(scale_data)

Encode to Vec<Bytes>

RuntimeConfiguration().update_type_registry(load_type_registry_preset("default"))
value = ['test', 'vec']
obj = RuntimeConfiguration().create_scale_object('Vec<Bytes>')
scale_data = obj.encode(value)
print(scale_data)

Add custom types to type registry

RuntimeConfiguration().update_type_registry(load_type_registry_preset("default"))

custom_types = {
    "types": {
        "MyCustomType": "u32",
        "CustomNextAuthority": {
          "type": "struct",
          "type_mapping": [
             ["AuthorityId", "AuthorityId"],
             ["weight", "AuthorityWeight"]
          ]
        }
    }   
}

RuntimeConfiguration().update_type_registry(custom_types)

Or from a custom JSON file

RuntimeConfiguration().update_type_registry(load_type_registry_preset("default"))
RuntimeConfiguration().update_type_registry(load_type_registry_file("/path/to/type_registry.json"))

Multiple runtime configurations

By default a singleton is used to maintain the configuration, for multiple instances:

# Kusama runtime config
runtime_config_kusama = RuntimeConfigurationObject()
runtime_config_kusama.update_type_registry(load_type_registry_preset("default"))
runtime_config_kusama.update_type_registry(load_type_registry_preset("kusama"))


# Polkadot runtime config
runtime_config_polkadot = RuntimeConfigurationObject()
runtime_config_polkadot.update_type_registry(load_type_registry_preset("default"))
runtime_config_polkadot.update_type_registry(load_type_registry_preset("polkadot"))

# Decode extrinsic using Kusama runtime configuration
extrinsic = runtime_config_kusama.create_scale_object(
    type_string='Extrinsic', 
    metadata=metadata_decoder
)
extrinsic.decode(ScaleBytes(extrinsic_data))

License

https://github.com/polkascan/py-scale-codec/blob/master/LICENSE