def get_coin_twitter_timeline(coin_id: str = "eth-ethereum") -> pd.DataFrame:
"""Get twitter timeline for given coin id. Not more than last 50 tweets [Source: CoinPaprika]
Parameters
----------
coin_id: str
id of coin from coinpaprika e.g. Ethereum - > 'eth-ethereum'
Returns
-------
pandas.DataFrame
Twitter timeline for given coin.
Columns: date, user_name, status, retweet_count, like_count
"""
session = PaprikaSession()
res = session.make_request(
session.ENDPOINTS["coin_tweeter"].format(coin_id))
if "error" in res:
console.print(res)
return pd.DataFrame()
if isinstance(res, list) and len(res) == 0:
return pd.DataFrame()
df = pd.DataFrame(res)[[
"date", "user_name", "status", "retweet_count", "like_count"
]]
df = df.applymap(lambda x: "\n".join(textwrap.wrap(x, width=80))
if isinstance(x, str) else x)
df["status"] = df["status"].apply(lambda x: x.replace(" ", ""))
df["date"] = df["date"].apply(lambda x: x.replace("T", "\n"))
df["date"] = df["date"].apply(lambda x: x.replace("Z", ""))
return df
def get_global_market() -> pd.DataFrame:
"""Return data frame with most important global crypto statistics like:
market_cap_usd, volume_24h_usd, bitcoin_dominance_percentage, cryptocurrencies_number,
market_cap_ath_value, market_cap_ath_date, volume_24h_ath_value, volume_24h_ath_date,
market_cap_change_24h, volume_24h_change_24h, last_updated. [Source: CoinPaprika]
Returns
-------
pandas.DataFrame
Most important global crypto statistics
Metric, Value
"""
session = PaprikaSession()
global_markets = session.make_request(session.ENDPOINTS["global"])
global_markets["last_updated"] = datetime.fromtimestamp(
global_markets["last_updated"]
)
for key, date in global_markets.items():
if "date" in key:
try:
global_markets[key] = parser.parse(date).strftime("%Y-%m-%d %H:%M:%S")
except (KeyError, ValueError, TypeError) as e:
console.print(e)
df = pd.Series(global_markets).to_frame().reset_index()
df.columns = ["Metric", "Value"]
return df
def get_list_of_exchanges(quotes: str = "USD") -> pd.DataFrame:
"""
List exchanges from CoinPaprika API [Source: CoinPaprika]
Parameters
----------
quotes: str
Comma separated quotes to return e.g quotes=USD,BTC
Returns
-------
pandas.DataFrame
rank, name, currencies, markets, fiats, confidence_score, reported_volume_24h,
reported_volume_7d ,reported_volume_30d, sessions_per_month,
"""
session = PaprikaSession()
exchanges = session.make_request(session.ENDPOINTS["exchanges"],
quotes=quotes)
df = pd.json_normalize(exchanges)
try:
df.columns = [
col.replace(f"quotes.{quotes}.", "")
for col in df.columns.tolist()
]
except KeyError as e:
logger.exception(str(e))
console.print(e)
df = df[df["active"]]
cols = [
"adjusted_rank",
"id",
"name",
"currencies",
"markets",
"fiats",
"confidence_score",
"reported_volume_24h",
"reported_volume_7d",
"reported_volume_30d",
"sessions_per_month",
]
df.loc[:, "fiats"] = df["fiats"].apply(
lambda x: len([i["symbol"] for i in x if x]))
df = df[cols]
df = df.applymap(lambda x: "\n".join(textwrap.wrap(x, width=28))
if isinstance(x, str) else x)
df.rename(
columns={
"adjusted_rank": "rank",
"confidence_score": "confidence"
},
inplace=True,
)
df.columns = [x.replace("reported_", "") for x in df.columns]
return df.sort_values(by="rank")
def get_coin(coin_id="eth-ethereum"):
"""Get coin by id
Parameters
----------
coin_id: str
id of coin from coinpaprika e.g. Ethereum - > 'eth-ethereum'
Returns
-------
dict with response
"""
session = PaprikaSession()
coin = session.make_request(session.ENDPOINTS["coin"].format(coin_id))
return coin
def get_list_of_coins() -> pd.DataFrame:
"""Get list of all available coins on CoinPaprika [Source: CoinPaprika]
Returns
-------
pandas.DataFrame
Available coins on CoinPaprika
rank, id, name, symbol, type
"""
session = PaprikaSession()
coins = session.make_request(session.ENDPOINTS["coins"])
df = pd.DataFrame(coins)
df = df[df["is_active"]]
return df[["rank", "id", "name", "symbol", "type"]]
def get_all_contract_platforms() -> pd.DataFrame:
"""List all smart contract platforms like ethereum, solana, cosmos, polkadot, kusama ... [Source: CoinPaprika]
Returns
-------
pandas.DataFrame
index, platform_id
"""
session = PaprikaSession()
contract_platforms = session.make_request(
session.ENDPOINTS["contract_platforms"])
df = pd.DataFrame(contract_platforms).reset_index()
df.columns = ["index", "platform_id"]
df["index"] = df["index"] + 1
return df
def get_coin_events_by_id(coin_id: str = "eth-ethereum") -> pd.DataFrame:
"""Get all events related to given coin like conferences, start date of futures trading etc. [Source: CoinPaprika]
Example of response from API:
.. code-block:: json
{
"id": "17398-cme-april-first-trade",
"date": "2018-04-02T00:00:00Z",
"date_to": "string",
"name": "CME: April First Trade",
"description": "First trade of Bitcoin futures contract for April 2018.",
"is_conference": false,
"link": "http://www.cmegroup.com/trading/equity-index/us-index/bitcoin_product_calendar_futures.html",
"proof_image_link": "https://static.coinpaprika.com/storage/cdn/event_images/16635.jpg"
}
.
Parameters
----------
coin_id: str
id of coin from coinpaprika e.g. Ethereum - > 'eth-ethereum'
Returns
-------
pandas.DataFrame
Events found for given coin
Columns: id, date , date_to, name, description, is_conference, link, proof_image_link
"""
session = PaprikaSession()
res = session.make_request(
session.ENDPOINTS["coin_events"].format(coin_id))
if not res or "error" in res:
return pd.DataFrame()
data = pd.DataFrame(res)
data["description"] = data["description"].apply(lambda x: "\n".join(
textwrap.wrap(x, width=40)) if isinstance(x, str) else x)
data.drop(["id", "proof_image_link"], axis=1, inplace=True)
for col in ["date", "date_to"]:
data[col] = data[col].apply(lambda x: x.replace("T", "\n")
if isinstance(x, str) else x)
data[col] = data[col].apply(lambda x: x.replace("Z", "")
if isinstance(x, str) else x)
return data
def get_contract_platform(platform_id: str = "eth-ethereum") -> pd.DataFrame:
"""Gets all contract addresses for given platform [Source: CoinPaprika]
Parameters
----------
platform_id: str
Blockchain platform like eth-ethereum
Returns
-------
pandas.DataFrame
id, type, active
"""
session = PaprikaSession()
contract_platforms = session.make_request(
session.ENDPOINTS["contract_platform_addresses"].format(platform_id))
return pd.DataFrame(contract_platforms)[["id", "type", "active"]]
def get_ohlc_historical(coin_id: str = "eth-ethereum",
quotes: str = "USD",
days: int = 90) -> pd.DataFrame:
"""
Open/High/Low/Close values with volume and market_cap. [Source: CoinPaprika]
Request example: https://api.coinpaprika.com/v1/coins/btc-bitcoin/ohlcv/historical?start=2019-01-01&end=2019-01-20
if the last day is current day it can an change with every request until actual close of the day at 23:59:59
Parameters
----------
coin_id: str
Paprika coin identifier e.g. eth-ethereum
quotes: str
returned data quote (available values: usd btc)
days: int
time range for chart in days. Maximum 365
Returns
-------
pandas.DataFrame
Open/High/Low/Close values with volume and market_cap.
"""
if quotes.lower() not in ["usd", "btc"]:
quotes = "USD"
if abs(int(days)) > 365:
days = 365
end = datetime.now().strftime("%Y-%m-%d")
start = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d")
session = PaprikaSession()
data = session.make_request(
session.ENDPOINTS["ohlcv_hist"].format(coin_id),
quotes=quotes,
start=start,
end=end,
)
if "error" in data:
console.print(data)
return pd.DataFrame()
return pd.DataFrame(data)
def get_coin_markets_by_id(coin_id: str = "eth-ethereum",
quotes: str = "USD") -> pd.DataFrame:
"""All markets for given coin and currency [Source: CoinPaprika]
Parameters
----------
coin_id: str
Coin Parpika identifier of coin e.g. eth-ethereum
quotes: str
Comma separated list of quotes to return.
Example: quotes=USD,BTC
Allowed values:
BTC, ETH, USD, EUR, PLN, KRW, GBP, CAD, JPY, RUB, TRY, NZD, AUD, CHF, UAH, HKD, SGD, NGN, PHP, MXN, BRL,
THB, CLP, CNY, CZK, DKK, HUF, IDR, ILS, INR, MYR, NOK, PKR, SEK, TWD, ZAR, VND, BOB, COP, PEN, ARS, ISK
Returns
-------
pandas.DataFrame
All markets for given coin and currency
"""
session = PaprikaSession()
markets = session.make_request(
session.ENDPOINTS["coin_markets"].format(coin_id), quotes=quotes)
if "error" in markets:
console.print(markets)
return pd.DataFrame()
data = []
for r in markets:
dct = {
"exchange": r.get("exchange_name"),
"pair": r.get("pair"),
"trust_score": r.get("trust_score"),
"pct_volume_share": r.get("adjusted_volume_24h_share"),
}
_quotes: dict = r.get("quotes")
for k, v in _quotes.items():
dct[f"{k.lower()}_price"] = v.get("price")
dct[f"{k.lower()}_volume"] = v.get("volume_24h")
dct["market_url"] = r.get("market_url")
data.append(dct)
return pd.DataFrame(data)
def get_coin_exchanges_by_id(coin_id="eth-ethereum"):
"""Get all exchanges for given coin id.
Parameters
----------
coin_id: Identifier of Coin from CoinPaprika
Returns
-------
pandas.DataFrame
id, name, adjusted_volume_24h_share, fiats
"""
session = PaprikaSession()
res = session.make_request(
session.ENDPOINTS["coin_exchanges"].format(coin_id))
df = pd.DataFrame(res)
df["fiats"] = df["fiats"].copy().apply(
lambda x: len([i["symbol"] for i in x if x]))
return df
def get_search_results(query: str,
category: Optional[Any] = None,
modifier: Optional[Any] = None) -> pd.DataFrame:
"""Search CoinPaprika. [Source: CoinPaprika]
Parameters
----------
query: str
phrase for search
category: Optional[Any]
one or more categories (comma separated) to search.
Available options: currencies|exchanges|icos|people|tags
Default: currencies,exchanges,icos,people,tags
modifier: Optional[Any]
set modifier for search results. Available options: symbol_search -
search only by symbol (works for currencies only)
Returns
-------
pandas.DataFrame
Search Results
Columns: Metric, Value
"""
session = PaprikaSession()
if category is None:
category = "currencies,exchanges,icos,people,tags"
data = session.make_request(session.ENDPOINTS["search"],
q=query,
c=category,
modifier=modifier,
limit=100)
results = []
for item in data:
category = data[item]
for r in category:
results.append({
"id": r.get("id"),
"name": r.get("name"),
"category": item,
})
return pd.DataFrame(results)
def get_exchanges_market(
exchange_id: str = "binance", quotes: str = "USD"
) -> pd.DataFrame:
"""List markets by exchange ID [Source: CoinPaprika]
Parameters
----------
exchange_id: str
identifier of exchange e.g for Binance Exchange -> binance
quotes: str
Comma separated quotes to return e.g quotes=USD,BTC
Returns
-------
pandas.DataFrame
pair, base_currency_name, quote_currency_name, market_url,
category, reported_volume_24h_share, trust_score,
"""
session = PaprikaSession()
data = session.make_request(
session.ENDPOINTS["exchange_markets"].format(exchange_id), quotes=quotes
)
if "error" in data:
console.print(data)
return pd.DataFrame()
cols = [
"exchange_id",
"pair",
"base_currency_name",
"quote_currency_name",
"category",
"reported_volume_24h_share",
"trust_score",
"market_url",
]
df = pd.DataFrame(data)
df["exchange_id"] = exchange_id
return df[cols]
def get_tickers_info_for_coin(coin_id: str = "btc-bitcoin",
quotes: str = "USD") -> pd.DataFrame:
"""Get all most important ticker related information for given coin id [Source: CoinPaprika]
.. code-block:: json
{
"id": "btc-bitcoin",
"name": "Bitcoin",
"symbol": "BTC",
"rank": 1,
"circulating_supply": 17007062,
"total_supply": 17007062,
"max_supply": 21000000,
"beta_value": 0.735327,
"first_data_at": "2010-11-14T07:20:41Z",
"last_updated": "2018-11-14T07:20:41Z",
"quotes": {
"USD": {
"price": 5162.15941296,
"volume_24h": 7304207651.1585,
"volume_24h_change_24h": -2.5,
"market_cap": 91094433242,
"market_cap_change_24h": 1.6,
"percent_change_15m": 0,
"percent_change_30m": 0,
"percent_change_1h": 0,
"percent_change_6h": 0,
"percent_change_12h": -0.09,
"percent_change_24h": 1.59,
"percent_change_7d": 0.28,
"percent_change_30d": 27.39,
"percent_change_1y": -37.99,
"ath_price": 20089,
"ath_date": "2017-12-17T12:19:00Z",
"percent_from_price_ath": -74.3
}
}
}
Parameters
----------
coin_id: str
Id of coin from CoinPaprika
quotes: str
Comma separated quotes to return e.g quotes = USD, BTC
Returns
-------
pandas.DataFrame
Most important ticker related information
Columns: Metric, Value
"""
session = PaprikaSession()
tickers = session.make_request(
session.ENDPOINTS["ticker_info"].format(coin_id), quotes=quotes)
for key, date in tickers.items():
if "date" in key or "data" in key:
try:
tickers[key] = parser.parse(date).strftime("%Y-%m-%d %H:%M:%S")
except (KeyError, ValueError, TypeError) as e:
logger.exception(str(e))
console.print(e)
if key == "quotes":
try:
tickers[key][quotes]["ath_date"] = parser.parse(
tickers[key][quotes]["ath_date"]).strftime(
"%Y-%m-%d %H:%M:%S")
except (KeyError, ValueError, TypeError) as e:
logger.exception(str(e))
console.print(e)
df = pd.json_normalize(tickers)
try:
df.columns = [col.replace("quotes.", "") for col in list(df.columns)]
df.columns = [
col.replace(".", "_").lower() for col in list(df.columns)
]
except KeyError as e:
logger.exception(str(e))
console.print(e)
df = df.T.reset_index()
df.columns = ["Metric", "Value"]
return df
def _get_coins_info_helper(quotes: str = "USD") -> pd.DataFrame:
"""Helper method that call /tickers endpoint which returns for all coins quoted in provided currency/crypto
{
"id": "btc-bitcoin",
"name": "Bitcoin",
"symbol": "BTC",
"rank": 1,
"circulating_supply": 17007062,
"total_supply": 17007062,
"max_supply": 21000000,
"beta_value": 0.735327,
"first_data_at": "2010-11-14T07:20:41Z",
"last_updated": "2018-11-14T07:20:41Z",
"quotes" : {
"USD": {
"price": 5162.15941296,
"volume_24h": 7304207651.1585,
"volume_24h_change_24h": -2.5,
"market_cap": 91094433242,
"market_cap_change_24h": 1.6,
"percent_change_15m": 0,
"percent_change_30m": 0,
"percent_change_1h": 0,
"percent_change_6h": 0,
"percent_change_12h": -0.09,
"percent_change_24h": 1.59,
"percent_change_7d": 0.28,
"percent_change_30d": 27.39,
"percent_change_1y": -37.99,
"ath_price": 20089,
"ath_date": "2017-12-17T12:19:00Z",
"percent_from_price_ath": -74.3
}
}
}
[Source: CoinPaprika]
Parameters
----------
quotes: Comma separated quotes to return e.g quotes=USD,BTC
Returns
-------
pandas.DataFrame
id, name, symbol, rank, circulating_supply, total_supply, max_supply, beta_value, first_data_at,
last_updated, price, volume_24h, volume_24h_change_24h, market_cap, market_cap_change_24h,
percent_change_15m, percent_change_30m, percent_change_1h, percent_change_6h, percent_change_12h,
percent_change_24h, percent_change_7d, percent_change_30d, percent_change_1y,
ath_price, ath_date, percent_from_price_ath
"""
session = PaprikaSession()
tickers = session.make_request(session.ENDPOINTS["tickers"], quotes=quotes)
data = pd.json_normalize(tickers)
try:
# data.columns = [col.replace(f"quotes.{quotes}.", f"{quotes.lower()}_") for col in data.columns.tolist()]
data.columns = [
col.replace(f"quotes.{quotes}.", "") for col in data.columns.tolist()
]
data.columns = [col.replace("percent", "pct") for col in list(data.columns)]
except KeyError as e:
console.print(e)
data.rename(
columns={
"market_cap_change_24h": "mcap_change_24h",
"pct_from_price_ath": "pct_from_ath",
},
inplace=True,
)
return data