messari package

Messari Class

class messari.messari.messari.Messari(api_key=None)

Bases: messari.dataloader.DataLoader

This class is a wrapper around the Messari API

Methods

get_all_assets([page, limit, asset_fields, ...])	Get the paginated list of all assets including metrics and profile.
get_all_markets([page, limit, to_dataframe])	Get the list of all exchanges and pairs that our WebSocket-based market real-time market data API supports.
get_asset(asset_slugs[, asset_fields, ...])	Get basic metadata for an asset.
get_asset_market_data(asset_slugs[, ...])	Get the latest market data for an asset.
get_asset_metrics(asset_slugs[, ...])	Get all the quantitative metrics for an asset.
get_asset_profile(asset_slugs[, ...])	Get all the qualitative information for an asset.
get_metric_timeseries(asset_slugs, asset_metric)	Retrieve historical timeseries data for an asset.
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_assets(page: int = 1, limit: int = 20, asset_fields: Optional[Union[str, List]] = None, asset_metric: Optional[str] = None, asset_profile_metric: Optional[str] = None, to_dataframe: Optional[bool] = None) → Union[Dict, pandas.core.frame.DataFrame]

Get the paginated list of all assets including metrics and profile.

Data is return only in JSON format when an asset profile is provided due to the high number of text fields. The keys of the object are assets and the value is the associated asset data.

The function can return a pandas DataFrame only when asset metric data is requested.

Parameters

page: int

Page number starting at 1. Increment value to paginate through results.

limit: int

Limit of assets to return. Default is 20, max value is 500.

asset_fields: str, list

Single filter string or list of fields to filter data. Available fields include:

• id

• name

• slug

• metrics

• profile

asset_metric: str

Single metric string to filter metric data. Available metrics include:

• market_data

• marketcap

• supply

• blockchain_stats_24_hours

• market_data_liquidity

• all_time_high

• cycle_low

• token_sale_stats

• staking_stats

• mining_stats

• developer_activity

• roi_data

• roi_by_year

• risk_metrics

• misc_data

• lend_rates

• borrow_rates

• loan_data

• reddit

• on_chain_data

• exchange_flows

• alert_messages

asset_profile_metric: str

Single profile metric string to filter profile data. Available metrics include:

• general

• contributors

• advisors

• investors

• ecosystem

• economics

• technology

• governance

• metadata

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_all_markets(page: int = 1, limit: int = 20, to_dataframe: bool = True) → Union[List[Dict], pandas.core.frame.DataFrame]

Get the list of all exchanges and pairs that our WebSocket-based market real-time market data API supports.

Parameters

page: int

Page number starting at 1. Increment value to paginate through results.

limit: int

Limit of assets to return. Default is 20, max value is 500.

to_dataframe: bool

Return data as DataFrame or list of dictionaries. Default is set to DataFrame.

Returns

list, DataFrame

List of dictionaries or pandas DataFrame of markets indexed by exchange slug.

get_asset(asset_slugs: Union[str, List], asset_fields: Optional[Union[str, List]] = None, to_dataframe: bool = True) → Union[Dict, pandas.core.frame.DataFrame]

Get basic metadata for an asset.

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin).

asset_fields: str, list

Single filter string or list of fields to filter data. Available fields include:

• id

• symbol

• name

• slug

to_dataframe: bool

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

Returns

dict, DataFrame

Dictionary or pandas DataFrame with asset metadata.

get_asset_market_data(asset_slugs: Union[str, List], to_dataframe: bool = True) → Union[Dict, pandas.core.frame.DataFrame]

Get the latest market data for an asset.

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin).

to_dataframe: bool

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

Returns

dict, DataFrame

Dictionary or pandas DataFrame with asset market data.

get_asset_metrics(asset_slugs: Union[str, List], asset_metric: Optional[str] = None, to_dataframe: bool = True) → Union[Dict, pandas.core.frame.DataFrame]

Get all the quantitative metrics for an asset.

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin).

asset_metric: str

Single metric string to filter metric data. Available metrics include:

• market_data

• marketcap

• supply

• blockchain_stats_24_hours

• market_data_liquidity

• all_time_high

• cycle_low

• token_sale_stats

• staking_stats

• mining_stats

• developer_activity

• roi_data

• roi_by_year

• risk_metrics

• misc_data

• lend_rates

• borrow_rates

• loan_data

• reddit

• on_chain_data

• exchange_flows

• alert_messages

to_dataframe: bool

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

Returns

dict, DataFrame

Dictionary or pandas DataFrame with asset metric data.

get_asset_profile(asset_slugs: Union[str, List], asset_profile_metric: Optional[str] = None) → Dict

Get all the qualitative information for an asset.

Data is return only in JSON format due to high number of text fields. The keys of the object are assets and the value is the associated asset data.

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin).

asset_profile_metric: str

Single profile metric string to filter profile data. Available metrics include:

• general

• contributors

• advisors

• investors

• ecosystem

• economics

• technology

• governance

• metadata

Returns

dict

Dictionary with asset profile data

get_metric_timeseries(asset_slugs: Union[str, List], asset_metric: str, start: Optional[str] = None, end: Optional[str] = None, interval: str = '1d', to_dataframe: bool = True) → Union[Dict, pandas.core.frame.DataFrame]

Retrieve historical timeseries data for an asset.

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin).

asset_metric: str

Single metric string to filter timeseries data. Available metrics include:

• blk.cnt

  The sum count of blocks created each day.

• txn.fee.avg

  The USD value of the mean fee per transaction.

• txn.cnt

  The sum count of transactions that interval. Transactions represent a bundle of intended actions to alter the ledger initiated by a user (human or machine). Transactions are counted whether they execute or not and whether they result in the transfer of native units.

• txn.tsfr.val.adj

  The sum USD value of all native units transferred removing noise and certain artifacts.

• sply.circ

  The circulating supply acknowledges that tokens may be held by projects/foundations which have no intent to sell down their positions, but which have not locked up supply in a formal contract. Thus, circulating supply does not include known project treasury holdings (which can be significant). Note that an investor must carefully consider both liquid and circulating supplies when evaluating an asset, and the two can vary significantly. A risk of depending entirely on circulating supply is that the number can change dramatically based on discretionary sales from project treasuries.

• mcap.circ

  The circulating marketcap is the price of the asset multiplied by the circulating supply. If no price is found for an asset because no trades occurred, the last price of the last trade is used. After 30 days with no trades, a marketcap of 0 is reported until trading resumes.

• reddit.subscribers

  The number of subscribers on the asset’s primary subreddit

• iss.rate

  The percentage of new native units (continuous) issued over that interval, extrapolated to one year (i.e., multiplied by 365), and divided by the current supply at the end of that interval. Also referred to as the annual inflation rate.

• mcap.realized

  The sum USD value based on the USD closing price on the day that a native unit last moved (i.e., last transacted) for all native units.

• bitwise.volume

  It is well known that many exchanges conduct wash trading practices in order to inflate trading volume. They are incentivized to report inflated volumes in order to attract traders. “Bitwise Volume” refers to the total volume over 10 exchanges identified by Bitwise to be free of wash trading activities. They tend to be regulated exchanges. However, that does not necessarily mean that the volume reported by other exchanges is 100% wash trades. As such, the Bitwise Volume underestimates the total volume.

• txn.tsfr.val.avg

  The sum USD value of native units transferred divided by the count of transfers (i.e., the mean “size” in USD of a transfer).

• act.addr.cnt

  The sum count of unique addresses that were active in the network (either as a recipient or originator of a ledger change) that interval. All parties in a ledger change action (recipients and originators) are counted. Individual addresses are not double-counted.

• fees.ntv

  The sum of all fees paid to miners in native units. Fees do not include new issuance.

• exch.flow.in.usd.incl

  The sum USD value sent to exchanges that interval, including exchange to exchange activity.

• blk.size.byte

  The sum of the size (in bytes) of all blocks created each day.

• txn.tsfr.val.med

  The median transfer value in US dollars.

• exch.flow.in.ntv.incl

  The amount of the asset sent to exchanges that interval, including exchange to exchange activity.

• exch.flow.out.usd

  The sum USD value withdrawn from exchanges that interval, excluding exchange to exchange activity.’

• txn.vol

  The sum USD value of all native units transferred (i.e., the aggregate size in USD of all transfers).

• fees

  The sum USD value of all fees paid to miners that interval. Fees do not include new issuance.

• exch.flow.out.ntv.incl

  The amount of the asset withdrawn from exchanges that interval, including exchange to exchange activity.

• exch.flow.out.usd.incl

  The sum USD value withdrawn from exchanges that interval, including exchange to exchange activity.

• txn.fee.med

  The USD value of the median fee per transaction.

• min.rev.ntv

  The sum of all miner revenue, which constitutes fees plus newly issued native units.

• exch.sply.usd

  The sum USD value of all native units held in hot or cold exchange wallets.

• diff.avg

  The mean difficulty of finding a hash that meets the protocol-designated requirement (i.e., the difficulty of finding a new block) that interval. The requirement is unique to each applicable cryptocurrency protocol.

• daily.shp

  The Sharpe ratio (performance of the asset compared to a “risk-free” asset) over a window of time).

• txn.tsfr.cnt

  The sum count of transfers that interval. Transfers represent movements of native units from one ledger entity to another distinct ledger entity. Only transfers that are the result of a transaction and that have a positive (non-zero) value are counted.

• exch.flow.in.ntv

  The amount of the asset sent to exchanges that interval, excluding exchange to exchange activity.

• new.iss.usd

  The sum USD value of new native units issued that interval. Only those native units that are issued by a protocol-mandated continuous emission schedule are included (i.e., units manually released from escrow or otherwise disbursed are not included).

• mcap.dom

  The marketcap dominance is the asset’s percentage share of total crypto circulating marketcap.

• daily.vol

  The annualized standard-deviation of daily returns over a window of time.

• reddit.active.users

  The number of active users on the asset’s primary subreddit

• exch.sply

  The sum of all native units held in hot or cold exchange wallets

• nvt.adj

  The ratio of the network value (or market capitalization, current supply) divided by the adjusted transfer value. Also referred to as NVT.

• exch.flow.out.ntv

  The amount of the asset withdrawn from exchanges that interval, excluding exchange to exchange activity.

• min.rev.usd

  The sum USD value of all miner revenue, which constitutes fees plus newly issued native units, represented as the US dollar amount earned if all native units were sold at the closing price on the same day.

• bitwise.price

  Volume weighted average price over Bitwise 10 exchanges.

• new.iss.ntv

  The sum of new native units issued that interval. Only those native units that are issued by a protocol-mandated continuous emission schedule are included (i.e., units manually released from escrow or otherwise disbursed are not included).

• blk.size.bytes.avg

  The mean size (in bytes) of all blocks created.

• hashrate

  The mean rate at which miners are solving hashes that interval.

• exch.flow.in.usd

  The sum USD value sent to exchanges that interval, excluding exchange to exchange activity.

• price

  Volume weighted average price computed using Messari Methodology

• real.vol

  It is well known that many exchanges conduct wash trading practices in order to inflate trading volume. They are incentivized to report inflated volumes in order to attract traders. “Real Volume” refers to the total volume on the exchanges that we believe with high level of confidence are free of wash trading activities. However, that does not necessarily mean that the volume reported by other exchanges is 100% wash trades. As such, the Messari “Real Volume” applies a penalty to these exchanges to discount the volume believed to come from wash trading activity. For more information, see our methodology page.

start: str

Starting date string for timeseries data. A default start date will provided if not specified.

end: str

Ending date string for timeseries data. A default end date will provided if not specified.

interval: str

Interval of timeseries data. Default value is set to 1d.

For any given interval, at most 2016 points will be returned. For example, with interval=5m, the maximum range of the request is 2016 * 5 minutes = 7 days. With interval=1h, the maximum range is 2016 * 1 hour = 84 days. Exceeding the maximum range will result in an error, which can be solved by reducing the date range specified in the request.

Anything under 1 day requires an enterprise subscription. Please email enterprise@messari.io for information.

Interval options include:

• 1m

• 5m

• 15m

• 30m

• 1hr

• 1d

• 1w

to_dataframe: bool

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

Returns

dict, DataFrame

Dictionary or pandas DataFrame of asset data.

DeFiLlama Class

class messari.defillama.defillama.DeFiLlama

Bases: messari.dataloader.DataLoader

This class is a wrapper around the DeFi Llama API

Methods

get_chain_tvl_timeseries(chains_in[, ...])	Retrive timeseries TVL for a given chain
get_current_tvl(asset_slugs)	Retrive current protocol tvl for an asset
get_global_tvl_timeseries([start_date, end_date])	Returns timeseries TVL from total of all Defi Llama supported protocols
get_protocol_tvl_timeseries(asset_slugs[, ...])	Returns times TVL of a protocol with token amounts as a pandas DataFrame.
get_protocols()	Returns basic information on all listed protocols, their current TVL and the changes to it in the last hour/day/week
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_chain_tvl_timeseries(chains_in: Union[str, List], start_date: Optional[Union[str, datetime.datetime]] = None, end_date: Optional[Union[str, datetime.datetime]] = None) → pandas.core.frame.DataFrame

Retrive timeseries TVL for a given chain

Parameters

chains_in: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin)

start_date: str, datetime.datetime

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

end_date: str, datetime.datetime

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

Returns

DataFrame

DataFrame containing timeseries tvl data for each chain

get_current_tvl(asset_slugs: Union[str, List]) → Dict

Retrive current protocol tvl for an asset

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin)

Returns

DataFrame

Pandas Series for tvl indexed by each slug {slug: tvl, …}

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

Returns timeseries TVL from total of all Defi Llama supported protocols

Parameters

start_date: str, datetime.datetime

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

end_date: str, datetime.datetime

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

Returns

DataFrame

DataFrame containing timeseries tvl data for every protocol

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

Returns times TVL of a protocol with token amounts as a pandas DataFrame. Returned DataFrame is indexed by df[protocol][chain][asset].

Parameters

asset_slugs: str, list

Single asset slug string or list of asset slugs (i.e. bitcoin)

start_date: str, datetime.datetime

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

end_date: str, datetime.datetime

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

Returns

DataFrame

pandas DataFrame of protocol TVL, indexed by df[protocol][chain][asset] to look at total tvl across all chains, index with chain=’all’ to look at total tvl across all tokens of a chain, asset=’totalLiquidityUSD’ tokens can be indexed by asset=’tokenName’ or by asset=’tokenName_usd’

get_protocols() → pandas.core.frame.DataFrame

Returns basic information on all listed protocols, their current TVL and the changes to it in the last hour/day/week

Returns

DataFrame

DataFrame with one column per DeFi Llama supported protocol