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cfe41ef7a9
* Combine CA peers to smiliar command * crypto/disc/top into one sdk function * Exchanges into sdk function * delete wrong platforms trail * #3478 sdk crypto load * Options hist 1 sdk function * SDK functions Co-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com>
427 lines
12 KiB
Python
427 lines
12 KiB
Python
"""CoinPaprika model"""
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__docformat__ = "numpy"
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import logging
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import textwrap
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from datetime import datetime
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import pandas as pd
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from dateutil import parser
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from openbb_terminal.cryptocurrency.coinpaprika_helpers import PaprikaSession
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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MARKETS_FILTERS = [
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"rank",
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"name",
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"symbol",
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"price",
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"volume_24h",
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"mcap_change_24h",
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"pct_change_1h",
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"pct_change_24h",
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"ath_price",
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"pct_from_ath",
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]
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EXMARKETS_FILTERS = [
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"pair",
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"base_currency_name",
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"quote_currency_name",
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"category",
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"reported_volume_24h_share",
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"trust_score",
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"market_url",
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]
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INFO_FILTERS = [
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"rank",
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"name",
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"symbol",
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"price",
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"volume_24h",
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"circulating_supply",
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"total_supply",
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"max_supply",
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"ath_price",
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"market_cap",
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"beta_value",
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]
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EXCHANGES_FILTERS = [
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"rank",
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"name",
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"currencies",
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"markets",
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"fiats",
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"confidence",
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"volume_24h",
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"volume_7d",
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"volume_30d",
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"sessions_per_month",
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]
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CONTRACTS_FILTERS = ["id", "type", "active"]
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@log_start_end(log=logger)
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def get_global_info() -> pd.DataFrame:
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"""Return data frame with most important global crypto statistics like:
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market_cap_usd, volume_24h_usd, bitcoin_dominance_percentage, cryptocurrencies_number,
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market_cap_ath_value, market_cap_ath_date, volume_24h_ath_value, volume_24h_ath_date,
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market_cap_change_24h, volume_24h_change_24h, last_updated. [Source: CoinPaprika]
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Returns
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-------
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pd.DataFrame
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Most important global crypto statistics
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Metric, Value
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"""
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session = PaprikaSession()
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global_markets = session.make_request(session.ENDPOINTS["global"])
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global_markets["last_updated"] = datetime.fromtimestamp(
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global_markets["last_updated"]
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)
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for key, date in global_markets.items():
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if "date" in key:
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try:
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if isinstance(date, datetime):
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new_date = date
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else:
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new_date = parser.parse(date)
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global_markets[key] = new_date.strftime("%Y-%m-%d %H:%M:%S")
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except (KeyError, ValueError, TypeError) as e:
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logger.exception(str(e))
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console.print(e)
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df = pd.Series(global_markets).to_frame().reset_index()
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df.columns = ["Metric", "Value"]
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return df
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@log_start_end(log=logger)
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def _get_coins_info_helper(symbols: str = "USD") -> pd.DataFrame:
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"""Helper method that call /tickers endpoint which returns for all coins quoted in provided currency/crypto
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{
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"id": "btc-bitcoin",
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"name": "Bitcoin",
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"symbol": "BTC",
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"rank": 1,
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"circulating_supply": 17007062,
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"total_supply": 17007062,
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"max_supply": 21000000,
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"beta_value": 0.735327,
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"first_data_at": "2010-11-14T07:20:41Z",
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"last_updated": "2018-11-14T07:20:41Z",
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"quotes" : {
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"USD": {
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"price": 5162.15941296,
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"volume_24h": 7304207651.1585,
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"volume_24h_change_24h": -2.5,
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"market_cap": 91094433242,
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"market_cap_change_24h": 1.6,
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"percent_change_15m": 0,
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"percent_change_30m": 0,
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"percent_change_1h": 0,
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"percent_change_6h": 0,
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"percent_change_12h": -0.09,
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"percent_change_24h": 1.59,
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"percent_change_7d": 0.28,
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"percent_change_30d": 27.39,
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"percent_change_1y": -37.99,
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"ath_price": 20089,
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"ath_date": "2017-12-17T12:19:00Z",
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"percent_from_price_ath": -74.3
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}
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}
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}
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[Source: CoinPaprika]
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Parameters
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----------
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symbols: Comma separated quotes to return e.g quotes=USD,BTC
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Returns
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-------
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pd.DataFrame
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id, name, symbol, rank, circulating_supply, total_supply, max_supply, beta_value, first_data_at,
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last_updated, price, volume_24h, volume_24h_change_24h, market_cap, market_cap_change_24h,
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percent_change_15m, percent_change_30m, percent_change_1h, percent_change_6h, percent_change_12h,
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percent_change_24h, percent_change_7d, percent_change_30d, percent_change_1y,
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ath_price, ath_date, percent_from_price_ath
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"""
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session = PaprikaSession()
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tickers = session.make_request(session.ENDPOINTS["tickers"], quotes=symbols)
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data = pd.json_normalize(tickers)
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try:
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data.columns = [
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col.replace(f"quotes.{symbols}.", "") for col in data.columns.tolist()
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]
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data.columns = [col.replace("percent", "pct") for col in list(data.columns)]
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except KeyError as e:
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logger.exception(str(e))
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console.print(e)
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data.rename(
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columns={
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"market_cap_change_24h": "mcap_change_24h",
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"pct_from_price_ath": "pct_from_ath",
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},
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inplace=True,
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)
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return data
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@log_start_end(log=logger)
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def get_coins_info(
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symbols: str = "USD", sortby: str = "rank", ascend: bool = True
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) -> pd.DataFrame: # > format big numbers fix
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"""Returns basic coin information for all coins from CoinPaprika API [Source: CoinPaprika]
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Parameters
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----------
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symbols: str
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Comma separated quotes to return e.g quotes=USD,BTC
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sortby: str
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Key by which to sort data
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ascend: bool
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Flag to sort data descending
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Returns
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-------
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pd.DataFrame
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rank, name, symbol, price, volume_24h, circulating_supply, total_supply,
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max_supply, market_cap, beta_value, ath_price,
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"""
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cols = [
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"rank",
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"name",
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"symbol",
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"price",
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"volume_24h",
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"circulating_supply",
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"total_supply",
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"max_supply",
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"market_cap",
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"beta_value",
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"ath_price",
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]
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df = _get_coins_info_helper(symbols)[cols]
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df = df.sort_values(by=sortby, ascending=ascend)
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return df
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@log_start_end(log=logger)
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def get_coins_market_info(
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symbols: str = "USD", sortby: str = "rank", ascend: bool = True
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) -> pd.DataFrame:
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"""Returns basic coin information for all coins from CoinPaprika API [Source: CoinPaprika]
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Parameters
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----------
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symbols: str
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Comma separated quotes to return e.g quotes=USD,BTC
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sortby: str
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Key by which to sort data
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ascend: bool
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Flag to sort data ascend
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Returns
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-------
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pd.DataFrame
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rank, name, symbol, price, volume_24h, mcap_change_24h,
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pct_change_1h, pct_change_24h, ath_price, pct_from_ath,
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"""
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cols = [
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"rank",
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"name",
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"symbol",
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"price",
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"volume_24h",
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"mcap_change_24h",
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"pct_change_1h",
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"pct_change_24h",
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"ath_price",
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"pct_from_ath",
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]
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df = _get_coins_info_helper(symbols=symbols)[cols].sort_values(by="rank")
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if sortby == "rank":
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df = df.sort_values(by=sortby, ascending=not ascend)
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else:
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df = df.sort_values(by=sortby, ascending=ascend)
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return df
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@log_start_end(log=logger)
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def get_list_of_exchanges(
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symbols: str = "USD", sortby: str = "rank", ascend: bool = True
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) -> pd.DataFrame:
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"""
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List exchanges from CoinPaprika API [Source: CoinPaprika]
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Parameters
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----------
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symbols: str
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Comma separated quotes to return e.g quotes=USD,BTC
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sortby: str
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Key by which to sort data
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ascend: bool
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Flag to sort data ascend
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Returns
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-------
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pd.DataFrame
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rank, name, currencies, markets, fiats, confidence_score, reported_volume_24h,
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reported_volume_7d ,reported_volume_30d, sessions_per_month,
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"""
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session = PaprikaSession()
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exchanges = session.make_request(session.ENDPOINTS["exchanges"], quotes=symbols)
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df = pd.json_normalize(exchanges)
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try:
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df.columns = [
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col.replace(f"quotes.{symbols}.", "") for col in df.columns.tolist()
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]
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except KeyError as e:
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logger.exception(str(e))
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console.print(e)
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df = df[df["active"]]
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cols = [
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"adjusted_rank",
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"id",
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"name",
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"currencies",
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"markets",
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"fiats",
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"confidence_score",
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"reported_volume_24h",
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"reported_volume_7d",
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"reported_volume_30d",
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"sessions_per_month",
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]
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df["fiats"] = df["fiats"].apply(lambda x: len([i["symbol"] for i in x if x]))
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df = df[cols]
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df = df.applymap(
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lambda x: "\n".join(textwrap.wrap(x, width=28)) if isinstance(x, str) else x
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)
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df = df.rename(
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columns={"adjusted_rank": "Rank", "confidence_score": "confidence"},
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)
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df.columns = [x.replace("reported_", "") for x in df.columns]
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if sortby.lower() == "rank":
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df = df.sort_values(by="Rank", ascending=not ascend)
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else:
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df = df.sort_values(by=sortby, ascending=ascend)
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return df
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@log_start_end(log=logger)
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def get_exchanges_market(
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exchange_id: str = "binance",
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symbols: str = "USD",
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sortby: str = "pair",
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ascend: bool = True,
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) -> pd.DataFrame:
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"""List markets by exchange ID [Source: CoinPaprika]
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Parameters
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----------
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exchange_id: str
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identifier of exchange e.g for Binance Exchange -> binance
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symbols: str
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Comma separated quotes to return e.g quotes=USD,BTC
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sortby: str
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Key by which to sort data
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ascend: bool
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Flag to sort data ascending
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Returns
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-------
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pd.DataFrame
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pair, base_currency_name, quote_currency_name, market_url,
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category, reported_volume_24h_share, trust_score,
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"""
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session = PaprikaSession()
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data = session.make_request(
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session.ENDPOINTS["exchange_markets"].format(exchange_id), quotes=symbols
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)
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if "error" in data:
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console.print(data)
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return pd.DataFrame()
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cols = [
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"exchange_id",
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"pair",
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"base_currency_name",
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"quote_currency_name",
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"category",
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"reported_volume_24h_share",
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"trust_score",
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"market_url",
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]
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df = pd.DataFrame(data)
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df["exchange_id"] = exchange_id
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df = df[cols]
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df = df.sort_values(by=sortby, ascending=ascend)
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return df
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@log_start_end(log=logger)
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def get_all_contract_platforms() -> pd.DataFrame:
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"""List all smart contract platforms like ethereum, solana, cosmos, polkadot, kusama ... [Source: CoinPaprika]
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Returns
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-------
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pd.DataFrame
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index, platform_id
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"""
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session = PaprikaSession()
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contract_platforms = session.make_request(session.ENDPOINTS["contract_platforms"])
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df = pd.DataFrame(contract_platforms).reset_index()
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df.columns = ["index", "platform_id"]
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# pylint: disable=unsupported-assignment-operation
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df["index"] = df["index"] + 1
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return df
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@log_start_end(log=logger)
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def get_contract_platform(
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platform_id: str = "eth-ethereum", sortby: str = "active", ascend: bool = True
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) -> pd.DataFrame:
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"""Gets all contract addresses for given platform [Source: CoinPaprika]
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Parameters
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----------
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platform_id: str
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Blockchain platform like eth-ethereum
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sortby: str
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Key by which to sort data
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ascend: bool
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Flag to sort data ascend
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Returns
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-------
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pd.DataFrame
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id, type, active
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"""
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session = PaprikaSession()
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contract_platforms = session.make_request(
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session.ENDPOINTS["contract_platform_addresses"].format(platform_id)
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)
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df = pd.DataFrame(contract_platforms)[["id", "type", "active"]]
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df = df.sort_values(by=sortby, ascending=ascend)
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return df
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