cryptodatapy.extract.adapters.vendors.defillama_adapter

Attributes

logger
data_cred

Classes

DefiLlamaAdapter

Adapter class for retrieving data from DefiLlama API.

Module Contents

cryptodatapy.extract.adapters.vendors.defillama_adapter.logger

cryptodatapy.extract.adapters.vendors.defillama_adapter.data_cred

class cryptodatapy.extract.adapters.vendors.defillama_adapter.DefiLlamaAdapter(config: Dict[str, Any] | None = None)

Bases: cryptodatapy.extract.adapters.base_adapter.BaseAPIAdapter

Adapter class for retrieving data from DefiLlama API. Implements the BaseAdapter contract via BaseAPIAdapter.

assets = None

fields = None

stablecoins = None

yields = None

_fetch_raw_meta(info_type: str) → Dict[str, Any]

Helper method to fetch raw metadata (chains, protocols, fees, etc.)

Parameters:

info_type (str) – The type of metadata to fetch (‘chains’, ‘protocols’, ‘fees’, ‘stablecoins’, ‘yields’).

Returns:

The raw metadata response from DefiLlama.

Return type:

Dict[str, Any]

get_chains_info(as_list: bool = False, remove_missing: list | None = None) → pandas.DataFrame | list

Get DefiLlama chains information.

Parameters:

• as_list (bool, default False) – If True, returns the chains information as a list.

• remove_missing (Optional[list], optional) – List of fields (column names) to check for missing values to filter out. Default is None.

Returns:

The requested chains information.

Return type:

Union[pd.DataFrame, list]

get_protocols_info(as_list: bool = False, remove_missing: list | None = None) → pandas.DataFrame | list

Get DefiLlama protocols information.

Parameters:

• as_list (bool, default False) – If True, returns the chains information as a list.

• remove_missing (Optional[list], optional) – List of fields (column names) to check for missing values to filter out. Default is None.

Returns:

The requested protocols information.

Return type:

Union[pd.DataFrame, list]

get_fees_info(as_list: bool = False, remove_missing: list | None = None) → pandas.DataFrame | list

Get DefiLlama fees information.

Parameters:

• as_list (bool, default False) – If True, returns the fees information as a list.

• remove_missing (Optional[list], optional) – List of fields (column names) to check for missing values to filter out. Default is None.

Returns:

The requested fees information.

Return type:

Union[pd.DataFrame, list]

get_stablecoins_info(as_list: bool = False, remove_missing: list | None = None) → pandas.DataFrame | list

Get DefiLlama stablecoins information.

Parameters:

• as_list (bool, default False) – If True, returns the stablecoins information as a list.

• remove_missing (Optional[list], optional) – List of fields (column names) to check for missing values to filter out. Default is None.

Returns:

The requested stablecoins information.

Return type:

Union[pd.DataFrame, list]

get_yields_info() → pandas.DataFrame | list

Get DefiLlama yields information.

Returns:

The requested yields information.

Return type:

Union[pd.DataFrame, list]

static _normalize_protocols(protocols_df: pandas.DataFrame) → pandas.DataFrame

Processes raw protocols endpoint data, selecting only high-value (Rating 4+) fields for identification, classification, and cross-referencing.

Parameters:

protocols_df (pd.DataFrame) – Raw protocols DataFrame from DefiLlama.

Returns:

Normalized protocols DataFrame.

Return type:

pd.DataFrame

static _normalize_chains(chains_df: pandas.DataFrame) → pandas.DataFrame

Normalizes the raw chain data, adds the ‘dataEndpoint’ tag, and applies manual ticker corrections (e.g., TRON -> TRX).

Parameters:

chains_df (pd.DataFrame) – Raw chains DataFrame from DefiLlama.

Returns:

Normalized chains DataFrame.

Return type:

pd.DataFrame

static _normalize_stablecoins(stablecoins_df: pandas.DataFrame) → pandas.DataFrame

Normalizes the raw stablecoins data.

Parameters:

stablecoins_df (pd.DataFrame) – Raw stablecoins DataFrame from DefiLlama.

Returns:

Normalized stablecoins DataFrame.

Return type:

pd.DataFrame

static _unify_assets(df_protocols: pandas.DataFrame, df_chains: pandas.DataFrame) → pandas.DataFrame

Merges and concatenates protocols and chains data, applying the slug hierarchy, resolving collisions, and establishing a canonical ticker precedence based on Type, Category, and TVL.

Parameters:

• df_protocols (pd.DataFrame) – Normalized protocols DataFrame.

• df_chains (pd.DataFrame) – Normalized chains DataFrame.

Returns:

Unified assets DataFrame with canonical tickers.

Return type:

pd.DataFrame

get_assets_info(as_list: bool = False) → pandas.DataFrame | list

Get DefiLlama assets information.

Note that DefiLlama does not have a direct “assets” endpoint. This method synthesizes the assets list by combining and normalizing data from the protocols and chains endpoints. It applies a hierarchy to resolve slugs and ticker collisions, establishing a canonical ticker based on asset type, category, and TVL.

Parameters:

as_list (bool, default False) – If True, returns the assets information as a list.

Returns:

The requested assets information.

Return type:

pd.DataFrame

get_fields_info(as_list: bool = False) → pandas.DataFrame | list

Gets DefiLlama fields information.

Parameters:

as_list (bool, default False) – If True, returns the fields information as a list.

Returns:

The requested fields information.

Return type:

pd.DataFrame

get_rate_limit_info() → Any | None

DefiLlama credits left in the api key, these reset on the 1st of each month.

_build_single_request_params(single_request_dict: Dict[str, Any]) → tuple[str, Dict[str, Any]]

Builds the URL and parameters for a single request object generated by the converter. This resolves the full path and query parameters for one API call.

Parameters:

single_request_dict (Dict[str, Any]) – A dictionary representing a single request with keys: - ‘endpoint’: The API endpoint path. - ‘slug’: The slug to append to the endpoint. - ‘query_params’: A dictionary of query parameters specific to this request.

Returns:

A tuple containing the full URL and the parameters dictionary for the request.

Return type:

tuple[str, Dict[str, Any]]

_fetch_all_raw_data(requests_list: List[Dict[str, Any]]) → List[Dict[str, Any]]

Fetches raw data for all requests in the list, implementing rate limiting.

Parameters:

requests_list (List[Dict[str, Any]]) – A list of request dictionaries generated by the converter.

Returns:

A list of raw data responses corresponding to each request.

Return type:

List[Dict[str, Any]]

_convert_params_to_vendor(data_req: cryptodatapy.core.data_request.DataRequest) → Dict[str, Any]

Converts the DataRequest object into the vendor’s specific API parameters. DefiLlama URLs rely heavily on protocol or chain name being part of the path.

Parameters:

data_req (DataRequest) – The standardized DataRequest object containing user-specified parameters.

Returns:

A dictionary of vendor-specific parameters including the full request list.

Return type:

Dict[str, Any]

_fetch_raw_data(params: Dict[str, Any]) → Dict[str, Any] | List[Dict[str, Any]]

Submits the vendor-specific parameters to the API and returns the raw responses.

Parameters:

params (Dict[str, Any]) – The vendor-specific parameters including the full request list.

Returns:

The raw data responses from DefiLlama.

Return type:

Union[Dict[str, Any], List[Dict[str, Any]]]

_transform_raw_response(data_req: cryptodatapy.core.data_request.DataRequest, raw_data: Any) → pandas.DataFrame

Processes the raw data responses into the package’s standardized tidy DataFrame format using the dedicated DefiLlamaWrangler.

Parameters:

• data_req (DataRequest) – The original DataRequest object.

• raw_data (Any) – The raw data response from DefiLlama.

Returns:

The transformed tidy DataFrame.

Return type:

pd.DataFrame