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Python SCALE Codec Library

Project description

Python SCALE Codec

Build Status Latest Version Supported Python versions License

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

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))

Using the type registry updater in your application

To ensure the type registries are in sync with the current runtime of the blockchain, you can use the updater function in your application:

from scalecodec.updater import update_type_registries

# Update type registries with latest version from Github   
try:
    update_type_registries()
except Exception:
    pass

This will overwrite the type registry JSON files with the downloaded lastest versions from Github. In case of write permission restrictions it is also possible to always use the remote version on Github with the use_remote_preset kwarg:

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

License

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

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