messari.tokenterminal package

Submodules

messari.tokenterminal.helpers module

This module is dedicated to helpers for the TokenTerminal class

messari.tokenterminal.helpers.response_to_df(response: Dict)

Transforms Token Terminal’s JSON response to pandas DataFrame

Parameters

resp – dict API JSON response

Returns

pandas DataFrame

messari.tokenterminal.tokenterminal module

This module is meant to contain the TokenTerminal class

class messari.tokenterminal.tokenterminal.TokenTerminal(api_key: str)

Bases: messari.dataloader.DataLoader

This class is a wrapper for the Token Terminal API

Methods

get_all_protocol_data([to_dataframe])	Returns an overview of latest data for all projects, ranging from metadata such as launch dates, logos brand colors and Twitter followers to more fundamental metrics such as Revenue, GMV, TVL and P/S ratios.
get_historical_metric_data(protocol_ids, metric)	Returns the time series of a specified metric for a given list of project.
get_project_ids()	Returns all the project ids available in Token Terminal
get_protocol_data(protocol_ids[, ...])	Returns a time series of the latest data for a given project, ranging from metadata such as Twitter followers to more fundamental metrics such as Revenue, GMV, TVL and P/S ratios.
get_response(endpoint_url[, params, headers])	Gets response from endpoint and checks for HTTP errors when requesting data.
set_api_dict(api_dict)	Sets a new dictionary to be used as an API key pair
set_taxonomy_dict(taxonomy_dict)	Sets a new dictionary to be used for taxonomy translations
translate(input_slugs)	Wrapper around messari.utils.validate_input, validate input & check if it's supported by DeFi Llama

get_all_protocol_data(to_dataframe=True)

Returns an overview of latest data for all projects, ranging from metadata such as launch dates, logos brand colors and Twitter followers to more fundamental metrics such as Revenue, GMV, TVL and P/S ratios.

The data is updated every 10 minutes.

Parameters

to_dataframe: bool

Return data as pandas DataFrame or JSON. Default is set to JSON.

Returns

——-

dict, DataFrame

Dictionary or pandas DataFrame of asset data.

get_historical_metric_data(protocol_ids: Union[str, List], metric: str, start_date: Optional[Union[str, datetime.datetime]] = None, end_date: Optional[Union[str, datetime.datetime]] = None) → pandas.core.frame.DataFrame

Returns the time series of a specified metric for a given list of project.

Parameters

protocol_ids: str, list

List of project IDs

metric: str

Single metric string to filter data. Available metrics include:

• price,

• market_cap

• market_cap_circulating

• market_cap_fully_diluted

• volume

• vol_mc

• pe

• ps

• tvl

• gmv

• revenue

• revenue_supply_side

• revenue_protocol

• token_incentives

start_date: str, datetime.datetime

Optional start date to set filter for timeseries (“YYYY-MM-DD”)

end_date: str, datetime.datetime

Optional end date to set filter for timeseries (“YYYY-MM-DD”)

Returns

DataFrame

pandas DataFrame with asset metric data.

get_project_ids()

Returns all the project ids available in Token Terminal

Returns

List

List of token ids.

get_protocol_data(protocol_ids: Union[str, List], start_date: Optional[Union[str, datetime.datetime]] = None, end_date: Optional[Union[str, datetime.datetime]] = None) → pandas.core.frame.DataFrame

Returns a time series of the latest data for a given project, ranging from metadata such as Twitter followers to more fundamental metrics such as Revenue, GMV, TVL and P/S ratios.

Parameters

protocol_ids: str, list

String of protocol ID

start_date: str, datetime.datetime

Optional start date to set filter for timeseries (“YYYY-MM-DD”)

end_date: str, datetime.datetime

Optional end date to set filter for timeseries (“YYYY-MM-DD”)

to_dataframe: bool

Return data as pandas DataFrame or JSON. Default is set to DataFrame.

Returns

——-

dict, DataFrame

Dictionary or pandas DataFrame of asset data.

Module contents

Module to handle initialization, imports, for TokenTerminal class