cryptodatapy.extract.getdata

Classes

GetData

Retrieves data from selected data source.

Module Contents

class cryptodatapy.extract.getdata.GetData(data_req: cryptodatapy.extract.datarequest.DataRequest, api_key: str | None = None)

Retrieves data from selected data source.

data_req

api_key = None

get_meta(attr: str = None, method: str = None, **kwargs) → pandas.DataFrame

Get metadata.

Parameters:

attr (str, {'categories', 'exchanges', 'indexes', 'assets', 'markets', 'market_types', 'fields', 'frequencies',) – ‘base_url’, ‘api_key’, ‘max_obs_per_call’, ‘rate_limit’}, default assets Gets the specified attribute or method from the data source object.
method (str, {'get_exchanges_info', 'get_indexes_info', 'get_assets_info', 'get_markets_info',) –

‘get_fields_info’, ‘get_frequencies_info’, ‘get_rate_limit_info’, ‘get_onchain_tickers_list’,
’get_top_mkt_cap_info’}

Gets the specified method from the data source object.
cat (str, optional, default None) – Category for which to return metadata, e.g. ‘crypto’, ‘fx’, ‘rates’, ‘macro’, etc.
exch (str, default 'binance') – Name of exchange for which to return metdata, e.g. ‘binance’, ‘ftx’, ‘kraken’, etc.
data_type (str, {'market', 'on-chain', 'off-chain'}, default None) – Type of data for which to return metadata, e.g. ‘on-chain’, ‘market’ or ‘off-chain’.
as_dict (bool, default False) – Returns attribute metadata as dictionary.
as_list (bool, default False) – Returns attribute metdata as list.

Returns:

meta – Metadata for selected attribute or method.

Return type:

Any

Examples

>>> data_req = DataRequest(source='ccxt')
>>> GetData(data_req).get_meta(attr='exchanges')
'['aax', 'alpaca', 'ascendex', 'bequant', 'bibox', 'bigone', 'binance', 'binancecoinm', 'binanceus', ...]'

>>> data_req = DataRequest(source='investpy')
>>> GetData(data_req).get_meta(attr='categories')
'['fx', 'rates', 'eqty', 'cmdty', 'macro']'

>>> data_req = DataRequest(source='ccxt')
>>> GetData(data_req).get_meta(method='get_assets_info')
                id          numericId       code        precision
ticker
1INCH           1INCH          None             1INCH           8
1INCHDOWN           1INCHDOWN      None         1INCHDOWN           8
1INCHUP         1INCHUP        None             1INCHUP         8
AAVE            AAVE           None             AAVE            8

get_series(method: str = 'get_data') → pandas.DataFrame

Get requested data.

Parameters:

method (str, {'get_data', 'get_ohlcv', 'get_indexes', 'get_onchain', 'get_social', 'get_trades', 'get_quotes',) –

‘get_funding_rates’, ‘get_open_interest’, ‘get_eqty’, ‘get_eqty_iex’, ‘get_etfs’, ‘get_stocks’,: ’get_fx’, ‘get_rates’, ‘get_cmdty’, ‘get_crypto’, ‘get_macro_series’}, default ‘get_data’

Gets the specified method from the data source object.

Returns:

df – DataFrame with DatetimeIndex (level 0), ticker (level 1), and field (cols) values.

Return type:

pd.DataFrame - MultiIndex

Examples

>>> data_req = DataRequest(source='ccxt', tickers=['btc', 'eth'], fields=['open', 'high', 'low', 'close',
                           'volume'], freq='d', exch='ftx', start_date='2017-01-01')
>>> GetData(data_req).get_series()
                        open        high        low         close       volume
date        ticker
2020-03-28      BTC             6243.25     6298.5          6028.0          6237.5          3888.9424
            ETH         128.995     133.0           125.11          131.04          1751.65972
2020-03-29      BTC             6233.5      6262.5          5869.5          5876.5          114076.5831
            ETH         130.98      131.84          123.81          124.33          138449.60906
2020-03-30      BTC             5876.0      6609.0          5856.0          6396.5          224231.1718

>>> data_req = DataRequest(source='glassnode', tickers=['btc', 'eth'],
                           fields=['add_act', 'tx_count', 'issuance'], freq='d', start_date='2016-01-01')
>>> GetData(data_req).get_series()
                        add_act     tx_count    issuance
date        ticker
2016-01-01      BTC             316489      123957          0.085386
            ETH         2350        8232            0.133048
2016-01-02      BTC             419389      148893          0.09197
            ETH         2410        9164            0.140147
2016-01-03      BTC             394047      142463          0.091947

async get_series_async(method: str = 'get_data_async') → pandas.DataFrame

Get requested data.

Parameters:: method (str, default 'get_data') – Gets the specified method from the data source object.
Returns:: df – DataFrame with DatetimeIndex (level 0), ticker (level 1), and field (cols) values.
Return type:: pd.DataFrame - MultiIndex

Examples

>>> data_req = DataRequest(source='ccxt', tickers=['btc', 'eth'], fields=['open', 'high', 'low', 'close',
                           'volume'], freq='d', exch='ftx', start_date='2017-01-01')
>>> GetData(data_req).get_series()
                        open        high        low         close       volume
date        ticker
2020-03-28      BTC             6243.25     6298.5          6028.0          6237.5          3888.9424
            ETH         128.995     133.0           125.11          131.04          1751.65972
2020-03-29      BTC             6233.5      6262.5          5869.5          5876.5          114076.5831
            ETH         130.98      131.84          123.81          124.33          138449.60906
2020-03-30      BTC             5876.0      6609.0          5856.0          6396.5          224231.1718

>>> data_req = DataRequest(source='glassnode', tickers=['btc', 'eth'],
                           fields=['add_act', 'tx_count', 'issuance'], freq='d', start_date='2016-01-01')
>>> GetData(data_req).get_series()
                        add_act     tx_count    issuance
date        ticker
2016-01-01      BTC             316489      123957          0.085386
            ETH         2350        8232            0.133048
2016-01-02      BTC             419389      148893          0.09197
            ETH         2410        9164            0.140147
2016-01-03      BTC             394047      142463          0.091947